From dwang at cse.ohio-state.edu Wed Nov 1 08:55:29 2017 From: dwang at cse.ohio-state.edu (WANG, DELIANG) Date: Wed, 1 Nov 2017 08:55:29 -0400 Subject: Connectionists: NEURAL NETWORKS, Nov. 2017 Message-ID: Neural Networks - Volume 95, November 2017 http://www.journals.elsevier.com/neural-networks Generation of low-gamma oscillations in a GABAergic network model of the striatum Zhihua Wu, Aike Guo, Xiaodi Fu Neural network for regression problems with reduced training sets Mohammad Bataineh, Timothy Marler Fast DCNN based on FWT, intelligent dropout and layer skipping for image retrieval Asma ElAdel, Mourad Zaied, Chokri Ben Amar Graph construction using adaptive Local Hybrid Coding scheme Fadi Dornaika, Mahdi Tavassoli Kejani, Alireza Bosaghzadeh Composite learning from adaptive backstepping neural network control Yongping Pan, Tairen Sun, Yiqi Liu, Haoyong Yu A multivariate extension of mutual information for growing neural networks Kenneth R. Ball, Christopher Grant, William R. Mundy, Timothy J. Shafer Graph-based composite local Bregman divergences on discrete sample spaces Takafumi Kanamori, Takashi Takenouchi Entropy factor for randomness quantification in neuronal data K. Rajdl, P. Lansky, L. Kostal Spiking neural P systems with multiple channels Hong Peng, Jinyu Yang, Jun Wang, Tao Wang, Zhang Sun, Xiaoxiao Song, Xiaohui Luo, Xiangnian Huang Global exponential stability of inertial memristor-based neural networks with time-varying delays and impulses Wei Zhang, Tingwen Huang, Xing He, Chuandong Li Learning in the machine: The symmetries of the deep learning channel Pierre Baldi, Peter Sadowski, Zhiqin Lu A patch-based convolutional neural network for remote sensing image classification Atharva Sharma, Xiuwen Liu, Xiaojun Yang, Di Shi From jeremiah.deng at otago.ac.nz Wed Nov 1 06:34:33 2017 From: jeremiah.deng at otago.ac.nz (Jeremiah Deng) Date: Wed, 1 Nov 2017 10:34:33 +0000 Subject: Connectionists: PAKDD-2018 Final Call for Papers Message-ID: <1509532473089.62994@otago.ac.nz> PAKDD-2018 Call for Papers The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD?18) June 3 ? 6, Melbourne, Australia | http://prada-research.net/pakdd18 Technical paper submission deadline: November 14th, 2017 [NEW] Dear Author(s), Now in its 22nd edition, the Pacific-Asia conference on Knowledge Discovery and Data Mining is the second oldest conference and a leading venue in the area of knowledge discovery and data mining (KDD). With a great pleasure, the Program Committee cordially invites original research and industrial application paper submission for the main technical track of the conference which will be held in Melbourne, Australia from June 3th to June 6th, 2018. Submission must be high-quality, original and previously unpublished research in the theory, practice, and application on all aspects of knowledge discovery, and data mining. Research papers reporting original real-world application problems and industrial papers reporting real-time mining applications and system development experience are also highly encouraged.? Submission deadline: November 14th, 2017 Notification of acceptance: January 28, 2018 Camera-ready: February 20, 2018 Conference date: June 3 - 6, 2018 The Pacific-Asia Conference on Knowledge Discovery and Data Mining?(PAKDD) provides an internationally prestigious forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications. The conference will also feature a high-quality and timely series of tutorials, and a wide range of workshops. Typically, the Program Committee will also select Best Paper Award, Best Student Paper Award and Best Application Award. The proceedings of the conference will be published by Springer as a volume of the LNAI series and a small number of selected papers will be invited for publications in special issues of high-quality journals including Knowledge and Information Systems (KAIS) and International Journal of Data Science and Analytics. Topics As a premier international conference on knowledge discovery and data mining, PAKDD?18 welcomes all submissions on all aspects of knowledge discovery, data mining and machine learning. Suggestive topics of relevance for the conference include, but not limited to, the following: - Theoretic foundations of KDD - Deep learning theory and applications in KDD - Novel models and algorithms - Statistical methods and graphical models for data mining - Anomaly detection and analytics - Association analysis - Clustering - Classification - Data pre-processing - Feature extraction and selection - Post-processing including quality assessment and validation - Mining heterogeneous/multi-source data - Mining sequential data - Mining spatial and temporal data - Mining unstructured and semi-structured data - Mining graph and network data - Mining social networks - Mining high dimensional data - Mining uncertain data - Mining imbalanced data - Mining dynamic/streaming data - Mining behavioral data - Mining multi-media data - Mining scientific data - Privacy preserving data mining - Fraud and risk analysis - Security and intrusion detection - Visual data mining - Interactive and online mining - Ubiquitous knowledge discovery and agent-based data mining - Integration of data warehousing, OLAP, and data mining - Parallel, distributed, and cloud-based high-performance data mining - Opinion mining and sentiment analysis - Human, domain, organizational, and social factors in data mining - Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, cyber-security, and industry-related problems Submission Policy Paper submission must be in English and adhere to the double-blind review policy. All papers will be double-blind reviewed by the Program Committee on the basis of technical quality, relevance to data mining, originality, significance, and clarity. All paper submissions will be handled electronically. Detailed instructions are provided on the conference home page. Papers that do not comply with the Submission Guidelines will be rejected without review. Each submitted paper should include an abstract up to 200 words and be no longer than 12 single-spaced pages with 10pt font size. Authors are strongly encouraged to use Springer LNCS/LNAI manuscript submission guidelines for their initial submissions. All papers must be submitted electronically through the paper submission system in PDF format only. One supplementary material file can be optionally submitted for review, although it will not be published in the proceeedings.? The submitted papers must not be previously published anywhere and must not be under consideration by any other conference or journal during the PAKDD review process. Submitting a paper to the conference means that if the paper was accepted, at least one author will attend the conference to present the paper. For no-show authors, their papers will not be included in the proceedings. Before submitting your paper, please carefully read and agree with the PAKDD submission policy and no-show policy: http://pakdd.org/policy.html. For more updated information and Calls for Tutorial proposal, Workshop Proposal and Data Mining Competition, please refer to our website at http://prada-research.net/pakdd18 Feel free to contact us at pakdd2018 at gmail.com if you have any questions; and we are excited to looking forward to welcoming you in Melbourne next year! Best Regards, Dinh Phung and Vincent S. Tseng Program Co-Chairs, PAKDD?18 (sent by Jeremiah Deng, PAKDD Publicity Co-Chair) From zfalomir at gmail.com Wed Nov 1 09:17:25 2017 From: zfalomir at gmail.com (Zoe Falomir) Date: Wed, 1 Nov 2017 14:17:25 +0100 Subject: Connectionists: Special Issue on Problem-solving, Creativity and Spatial Reasoning in Cognitive Systems (ProSocrates) (15 Nov) Message-ID: Special Issue on Problem-solving, Creativity and Spatial Reasoning in Cognitive Systems (ProSocrates) @ Cognitive Systems Research, Elsevier The focus of this ProSocrates Special Issue is to bring problem-solving, spatial cognition/reasoning, cognitive systems and creativity disciplines together, by bringing in dialogue specialists from each of the fields. Authors of experimental, theoretical and computational work which combines perspectives from at least 2 these topics are invited to submit contributions. The larger aim of integrating these topics is to produce theoretical tools, approaches and methodologies for creative and spatial problem solving in cognitive systems, in a manner that would benefit from such interdisciplinary bootstrapping. Papers included in this issue will address such questions/debates as: How spatial reasoning can help in problem solving? How can problems be modeled in order to be solved creatively? How can spatial reasoning improve cognitive and/or creative skills in people? and in cognitive systems? What is the relation between Creativity and Spatial Reasoning? How sketches, shapes and colours can be interpreted cognitively and/or creatively? What is the relation between computational creativity, cognitive creativity and reasoning? How analogy and metaphor, image schemas and concept blending shed light on creative problem solving? Possible topics to be explored by the contributions to this special issue include: Spatial cognition, creative cognition Spatial reasoning, case-based reasoning, analogical reasoning General and spatial problem solving, knowledge representation for problem-solving, cross-modal creativity and problem solving Analogy and metaphor, concept blending, image schemas Cognitive modeling and qualitative modeling Computational creativity, computational cognitive systems Symbolic, subsymbolic and hybrid approaches, evolutionary approaches and genetic algorithms Systems for enhancing human spatial reasoning and/or creativity Cognitive recommender systems, natural and artificial cognitive systems Visuospatial creativity, insight and re-representation Applications in Education, Robotics, Design, etc. SUBMISSION GUIDELINES Submissions to the special issue must include original research. Papers must be new and have not been published or submitted to other journals. Authors should prepare their manuscript according to the "Guide for Authors" available at the journal homepage: http://www.journals.elsevier.com/cognitive-systems-research/. Submission should be made via the EVISE system: https://www.evise.com/profile/api/navigate/COGSYS Authors must select ?VSI: ProSocrates? when they reach the "Article Type" step in the submission process. All papers will be peer-reviewed following the reviewing procedures of the Cognitive Systems Research (CSR) journal. All papers will undergo a preliminary screening to ensure relevance to the special issue prior to be the peer-review phase; research papers that do not sufficiently address the special issue call may not be selected for a full peer review (such a decision will be communicated rapidly). IMPORTANT DATES Deadline for paper submission: November 15th, 2017 Notification of acceptance: July 15th, 2018 Publication date: September 15th, 2018 GUEST EDITORS Zoe Falomir University of Bremen, Bremen Spatial Cognition Centre, Germany zfalomir at uni-bremen.de http://cosy.informatik.uni-bremen.de/staff/zoe-falomir-llansola Ana-Maria Olte?eanu University of Bremen, Bremen Spatial Cognition Centre, Germany amoodu at informatik.uni-bremen.de http://cosy.informatik.uni-bremen.de/staff/ana-maria-olteteanu -- Kind regards, Dr.-Ing. Zoe Falomir ------------------------------------------------------------ Dr.-Ing. Zoe Falomir Llansola https://sites.google.com/site/zfalomir/home Twitter @zfalomir CogQDA project Twitter @CogQDA Spatial Cognition Research Centre Universit?t Bremen B?ro: Cartesium 3.54 Enrique-Schmidt-Str. 5 28359 Bremen Phone + 49 (0) 421-218-64282 Fax + 49 (0) 421-218-64239 ------------------------------------------------------------ -- ------------------------------------------------------------ Dr.-Ing. Zoe Falomir Llansola https://sites.google.com/site/zfalomir/home Twitter at @zfalomir ------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From dengdehao at gmail.com Wed Nov 1 05:53:44 2017 From: dengdehao at gmail.com (Teng Teck Hou) Date: Wed, 1 Nov 2017 17:53:44 +0800 Subject: Connectionists: [INNS-BDDL 2018] Call for Papers Message-ID: <59f999a8.cd44620a.cae09.168f@mx.google.com> [Apologies for cross-postings] ########################################################### CALL FOR PAPERS The 3rd INNS Conference on Big Data and Deep Learning 2018 April 17-19, 2018, Bali, Indonesia Homepage: http://www.innsbigdata2018.org #######################Description:###################### The International Neural Network Society (INNS) is the premiere organization for individuals interested in a theoretical and computational understanding of the brain and applying that knowledge to develop new and more effective forms of machine intelligence. INNS was formed in 1987 by the leading scientists in the neural network field. Researchers and colleagues who work in the area of big data and machine learning, we are happy to announce "The 3rd INNS Conference on Big Data and Deep Learning (INNS BDDL) will be held Tuesday through Thursday, April 17 ? 19, 2018 at the Grand Inna Bali Beach hotel, Sanur, Bali, Indonesia. The INNS BDDL conference aims to create a valuable and important forum for scientists and engineers throughout the world to present the latest research findings and idea at the forefront of Big Data and Deep Learning." Accepted and presented papers will be published in Procedia Computer Science indexed by Scopus. Several papers will be selected for possible publication in a high-quality journal. A preliminary list of such journals includes: - Cognitive Systems Research (Scopus SJR 0.648, Impact Factor 1.182) - Cognitive Computation (Scopus SJR 0.823, Impact Factor 3.441) - Big Data Analytics - Evolving Systems (Scopus SJR 0.459, Impact Factor 1.067) - International Journal of Neural Systems (Scopus SJR 1.121, Impact Factor 6.333) - and possibly others Several papers will be selected for possible publication in top journals. The conference will feature a comprehensive technical program with technical tracks on: Track 1: Big Data Track 2: Big Data Algorithms Track 3: Deep Learning Track 4: Application Areas ####################Important Dates################################# * Tutorial and workshop proposals (Submission) ?30 September 2017 * Tutorial and workshop proposals (Decision) ? 7 October 2017 * Paper submission ???? 1 December 2017 * Decision notification???? 8 January 2018 * Camera-ready submission??? 2 February 2018 * Conference????? 17 - 19 April 2018 ################################################################### #########################Keynote Speakers########################## * Geoffrey I. Webb, Monash University, Australia * Kay Chen Tan, City University, Hong Kong * Ari Santoso, Ministry of Education and Culture ################################################################### #################### Organizing committees ############### General chairs Seiichi Ozawa, Kobe University, Japan Ah-Hwee Tan, Nanyang Technological University, Singapore Program Chairs Plamen P. Angelov, Lancaster University, UK Asim Roy, Arizona State University, USA Mahardhika Pratama, Nanyang Technological University, Singapore Honorary Board Mohammad Nuh, Institut Teknologi Sepuluh Nopember, Indonesia Joni Hermana, Institut Teknologi Sepuluh Nopember, Indonesia Heru Setyawan, Institut Teknologi Sepuluh Nopember, Indonesia Local Committee Chairs Dieky Adzkiya, Institut Teknologi Sepuluh Nopember, Indonesia Advisory Board Yew-Soon Ong, Nanyang Technological University, Singapore Robert Kozma, University of Memphis, USA Sankar K. Pal, Indian Statistical Institute, India Haibo He, University of Rhode Island, USA Witold Pedrycz, University of Alberta, Alberta, Canada Leszek Rutkowski, Czestochowa University of Technology, Poland Nikola Kasabov, Auckland University of Technology, New Zealand Fernando Gomide, University of Campinas, Brazil Marley Vellasco, Pontif?cia Universidade Cat?lica do Rio de Janeiro, Brazil Yoonsuck Choe, Texas A&M University Minho Lee, Kyungpook National University, South Korea Bao-Liang Lu, Shanghai Jiao Tong University, China Irwin King, the Chinese University of Hong Kong, Hong Kong Tutorials/Workshop Chairs Igor Skrjanc, University of Ljubljana, Slovenia Sundaram Suresh, Nanyang Technological University, Singapore Noor Akhmad Setiawan, Universitas Gadjah Mada, Indonesia Poster Sessions Chairs Eko Setiadji, Institut Teknologi Sepuluh Nopember, Indonesia Agus Salim, La Trobe University, Australia Ali Ridho Barakbah, Politeknik Elektronika Negeri Surabaya, Indonesia Special Sessions Chairs Justin Wang, La Trobe University, Australia Yongping Pan, National University of Singapore, Singapore Alfian Futhul Hadi, Universitas Jember, Indonesia Panel Chairs Sreenatha Anavatti, University of New South Wales, Australia Mukesh Prasad, University of Technology, Sydney, Australia Achmad Affandi, Institut Teknologi Sepuluh Nopember, Indonesia Awards Chairs Tapabrata Ray, University of New South Wales, Australia Dejan Dovzan, University of Ljubljana, Slovenia Richard J. Oentaryo, McLaren Applied Technologies, Singapore Publication Chairs Edwin Lughofer, Johannes Kepler University, Austria Jose Antonio Iglesias, Carlos III University of Madrid, Spain Moamar Sayed?Mouchaweh, Institute Mines Telecom Lille Douai, France Publicity Chair Simone Scardapane, Sapienza University, Italy Teng Teck Hou, Singapore Management University, Singapore Kurnianingsih, Politeknik Negeri Semarang, Indonesia International Liaison Chairs Yun Sing Koh, University of Auckland, New Zealand Deepak Puthal, University of Technology Sydney, Australia Wirawan, Institut Teknologi Sepuluh Nopember, Indonesia Webmaster Mohamad Abdul Hady, Institut Teknologi Sepuluh Nopember, Indonesia Andri Ashfahani, Institut Teknologi Sepuluh Nopember, Indonesia Choiru Za?in, La Trobe University, Australia ########################################################## ###### Topics and Areas include, but not limited to the following###### >>BIG DATA Autonomous, online, incremental learning in big data High dimensional data, feature selection, feature transformation for big data Scalable algorithms for big data Big data analytics Data stream analytics Parallel & distributed computing for big data analytics (cloud, map-reduce, etc.) Online learning Online multimedia/stream/text analytics Link and graph mining Big data and cloud computing, large scale stream processing on the cloud Big data and collective intelligence/collaborative learning Big data and hybrid systems Big data and self-aware systems Big data and infrastructure Big data visualization? >>Big Data Algorithm Neuromorphic hardware for scalable machine learning Evolving systems for big data analytics Evolutionary systems and big data Fuzzy systems and big data Cognitive modelling and big data Probabilistic approach for big data Concept drift detection for big data Granular computing for big data Transfer learning for big data >>Deep Learning Deep belief network Convolutional neural network Long short term memory Deep network architecture Deep autoencoder Deep stacked network Deep learning for natural language processing Deep learning for machine vision Evolving deep network Transfer learning in deep learning Online deep learning >>Application Areas Banking and Securities Communications, Media and Entertainment Healthcare Providers Education Manufacturing & Natural Resources Government Insurances Retail & Wholesale Trade Transportation Energy & Utilities, Etc. ############################################################################ ##########################Sponsoring Organizations################# * INNS - International Neural Network Society * MTC - Mechatronic Technology Center, Institut Tecknologi Sepuluh Nopember ################################################################ Previous INNS Conference: INNS 2016 in Thessaloniki, Greece INNS 2015 in San Francisco, USA -------------- next part -------------- An HTML attachment was scrubbed... URL: From dtborek at gmail.com Wed Nov 1 14:38:26 2017 From: dtborek at gmail.com (Daniel Borek) Date: Wed, 1 Nov 2017 19:38:26 +0100 Subject: Connectionists: Late Bird call for the AoN Brainhack Warsaw [17-19th November 2017] Message-ID: *AoN Brainhack Warsaw 2017* *November 17-19, 2017* *University of Warsaw, Warsaw, Poland* *? The blitz Late Bird registration open until 7th November 2017 ?* On the weekend of *17-19th November 2017*, the first edition of AoN Brainhack Warsaw will take place. During this three-day event dedicated to students and PhD students, we will work in teams on* neuroscience-related projects*. The aim of the event is to meet new, enthusiastic researchers, make new friendships in academia, learn, share the knowledge on data mining and brain research, but also promote open science in the spirit of the whole Brainhack community ( Craddock et al., 2016) . Attendees of various backgrounds are welcome to join! At the moment we are opening the Late Bird registration for project participants, which closes on 7th November 2017. Some of the projects got fully booked already and since they have limitations in terms of the number of participants, these projects have been closed for this round of registration. Please look at the list of the currently available projects : - Functional connectivity research: can we find a common ground? - Development of video game for studying joint action dynamics - Hypothesis?-driven white matter tractography from T1?-weighted MRI images - One channel EEG sleep staging with open source and open hardware NeuroOn sleep mask - Building and using the ?FlyPi?: the 3D-printed Neurobiology Lab - Unfolding the Subcortex *All the applications which we received after the end of Early Bird phase, will be automatically considered as the Late Bird applications.* The applications will be reviewed and the notification of acceptance will be sent to the applicants until 10th October2017. A registration fee of *30EUR* (or 120PLN) will be requested upon acceptance. The registration fee will be spent on the catering during the event. In order to register, please visit our website and learn more about AoN Brainhack Warsaw! https://brainhackwarsaw.github.io/ We are looking forward to see you in Warsaw! *The AoN Brainhack Warsaw 2017 team* -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.jolivet at ucl.ac.uk Thu Nov 2 05:01:07 2017 From: r.jolivet at ucl.ac.uk (Jolivet, Renaud) Date: Thu, 2 Nov 2017 09:01:07 +0000 Subject: Connectionists: MCAA Academy: Call for Mentors Message-ID: <9043F68E-053F-4DD0-BC2F-A062620145AB@ucl.ac.uk> Dear list, Please find below a call for mentors for a new program of the Marie Curie Alumni Association (MCAA) affiliated with EU institutions. MCAA Academy is a new program to support the career development of its members. Mentoring is at the core of the program. Our advanced mentoring platform provides a continuous, full-spectrum learning experience, allowing mentees to focus on the skills that matter the most, when they matter the most. We are seeking outstanding professionals to mentor MCAA members using this platform. Mentors are expected to have achieved an advanced stage in their career and be willing to provide leadership and advice to our members. The program will run for 6 months and will require up to 1 hour face time per month. Mentors and mentees will be matched according to their skills, interests and career goals. Do you want to become a mentor? Complete the registration form at https://www.mariecuriealumni.eu/form/mcaa-academy-call-mentors. Want to know more about the Marie Curie Alumni Association, visit https://www.mariecuriealumni.eu/. Regards, Renaud Jolivet ? Prof. Renaud Jolivet University of Geneva, Physics Section CERN, Experimental Physics Department +41 79 830 2129 (mobile) +41 22 379 6275 (UNIGE) +41 22 767 2470 (CERN) renaud.jolivet at unige.ch linkedin.com/in/renaud-jolivet-63b5534 https://scholar.google.ch/citations?user=9Ozwv7EAAAAJ&hl=en -------------- next part -------------- An HTML attachment was scrubbed... URL: From Phil.Garner at idiap.ch Thu Nov 2 06:19:56 2017 From: Phil.Garner at idiap.ch (Phil Garner) Date: Thu, 2 Nov 2017 11:19:56 +0100 Subject: Connectionists: Post-doctoral positions in deep learning for speech processing Message-ID: Dear Colleagues, We currently have openings for two post-doctoral researchers at Idiap Research Institute. Both involve the theory and application of deep learning to bring speech processing to home devices. http://www.idiap.ch/education-and-jobs/job-10232 Idiap is located in French speaking Switzerland, although the lab hosts many nationalities, and functions in English. All positions offer quite generous salaries. The positions involve collaboration with a commercial partner located nearby. However, they are funded by a Swiss federal grant, so a significant research element is expected. Several similar positions at PhD, post-doc and senior level are available at the institute in general. http://www.idiap.ch/en/join-us/job-opportunities Sincerely, -- Phil Garner http://www.idiap.ch/~pgarner From Pavis at iit.it Thu Nov 2 07:19:59 2017 From: Pavis at iit.it (Pavis) Date: Thu, 2 Nov 2017 11:19:59 +0000 Subject: Connectionists: Call for Postdoctoral position in Machine Learning for biomedical image analysis - 74477 In-Reply-To: <0E09F354EB71FC40A4D51EE54D8A9C88BDF7AAD4@IITMXWGE015.iit.local> References: <0E09F354EB71FC40A4D51EE54D8A9C88BDF7AAD4@IITMXWGE015.iit.local> Message-ID: <0E09F354EB71FC40A4D51EE54D8A9C88BDF7AFB2@IITMXWGE015.iit.local> Postdoctoral position in Machine Learning for biomedical image analysis BC 74477 Workplace: Genova, Italy Expires on November 15th, 2017 The Pattern Analysis and Computer Vision (PAVIS, http://pavis.iit.it/) department and the Visual Geometry and Modelling (VGM, http://vgm.iit.it/) Research Line at Istituto Italiano di Tecnologia are looking for a highly motivated full-time post-doc (1 year duration) to work on a biomedical imaging project related to blood smears image analysis. The candidate will consolidate PAVIS/VGM expertise in the research area of image analysis for cells detection, segmentation and classification. The research theme is related to the development of a highly efficient medical application in collaboration with an industrial partner. The focus will be on the creation of a software tool inspecting stained blood films for the detection and classification of blood white cells based on their morphological characterization. This implies the development of ad-hoc algorithms for detection and classification of cells based on machine learning methods and in particular exploiting deep learning state-of-the-art models. The inspection problem will also require the investigation of standard classification approaches based on visual-feature, exploiting therefore feature extraction and selection methods. The ideal candidates for this position has a Ph.D. in machine learning, computer vision or related areas, and research experience and qualification should be within the following subjects: image analysis, cells detection and segmentation, machine learning, deep learning, feature extraction. Strong programming skill are highly required, preferably with good knowledge of Matlab, Python and C/C++ languages. Evidence of high quality research on the above specified areas in the form of published papers in top conferences/journals and/or patents will be duly considered. Salary will be commensurate to qualification and experience and in line with international standard. Further details and informal enquires can be made by email to pavis at iit.it quoting BIO-PD 74477 as reference number in the subject. Please send your application, including a curriculum vitae (possibly with a pdf of your most representative publications) a research statement also describing your previous research experience and outlining its relevance to the call topics and the names of 2 referees, to pavis at iit.it, quoting ?BIO-PD 74477? as reference number. This call will remain open and applications will be reviewed until the position is filled, but for full consideration please apply by November 15, 2017. Please note that this position is contingent on budget approval. Istituto Italiano di Tecnologia (IIT), with its headquarters in Genova, Italy, is a non-profit institution with the primary goal of creating and disseminating scientific knowledge and strengthening Italy?s technological competitiveness. The institute offers state-of-the-art equipment and a top-level interdisciplinary research environment focused on robotics and computer vision, neuroscience, drug discovery, nanoscience and technology. In order to comply with the Italian law (art. 23 of Privacy Law of the Italian Legislative Decree n. 196/03), we have to kindly ask the candidate to give his/her consent to allow IIT to process his/her personal data. We inform you that the information you provide will be used solely for the purpose of assessing your professional profile to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, with headquarters in Genoa, Via Morego 30, acting as the Data Holder, using computer and paper based means, observing the rules on protection of personal data, including those relating to the security of data. Please also note that, pursuant to art.7 of Legislative Decree 196/2003, you may exercise your rights at any time as a party concerned by contacting the Data Manager. Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce. From aeck at oberlin.edu Thu Nov 2 09:07:24 2017 From: aeck at oberlin.edu (Adam Eck) Date: Thu, 2 Nov 2017 09:07:24 -0400 Subject: Connectionists: CFP: BigSurv18 (Big Data, Data Science, and Survey Science) Message-ID: <8B0DC023-9955-47D5-8FD9-A65A34D4BAE9@oberlin.edu> ##################################################### CALL FOR PAPERS: BigSurv18 The International Conference on Big Data Meets Survey Science October 25-27, 2018 Barcelona, Spain https://www.bigsurv18.org/ ##################################################### Explore new statistical frontiers at the intersection of survey science and big data! +++++++++++++++++ Aim and Scope +++++++++++++++++ Attention Computer Scientists, Data Scientists, and Survey Scientists, The first international conference on Big Data Meets Survey Science (BigSurv18) is currently accepting abstracts for presentation at the conference on the theme ?Exploring New Statistical Frontiers at the Intersection of Survey Science and Big Data.? BigSurv18 will be held October 25?27, 2018, at the Research and Expertise Centre for Survey Methodology at the Universitat Pompeu Fabra in Barcelona, Spain. The conference offers an opportunity to address the ongoing paradigm shift in how researchers produce, analyze, and use statistics. The event, hosted by the European Survey Research Association (ESRA), is intended to foster communication, collaboration, and understanding between two groups: (1) computer and data scientists focusing on emerging Big Data sources and analysis techniques and (2) methodologists and researchers working on traditional sources of data collection and statistical analyses, By combining efforts, we can identify and overcome academic divides and make unified survey and ?Big Survey Data? population inference a reality. We invite presenters from the various disciplines and around the world to submit an abstract for presentation at the conference. In addition, to accommodate differences in publication objectives and cultures across the disciplinespapers will be eligible for consideration in one of two publication outlets: A. An edited conference volume to be published by John Wiley & Sons in 2019. B. A special issue of a peer-reviewed computer science-oriented journal to be published immediately following the conference (journal still to be decided). In your submission, please indicate (1) if you would like your paper to be considered for publication and (2) state your preferred publication outlet. We will do our best to accommodate your request. When we notify you about whether your abstract was accepted, we will also let you know if you are under further consideration for one of these two publication venues. ++++++++++++++++++ Topics of Interest ++++++++++++++++++ To be considered for the conference, presentations and papers should be broad and forward-looking; they may be original research or syntheses of the state of the art. The following are examples of topics that are of particular interest: - Using Big Data sources?such as data from social networks, traditional business systems, and the Internet of Things?in statistics production - Measuring new phenomena in society using Big Data - Discussing methods for combining Big Data with traditional data sources - Using data mining and machine learning methods to develop and understand population statistics - Methods within machine learning for modelling human behaviors - Assessing new data processing and analytical tools for Big Data - Implementing data visualization methods for Big Data - Designing of interfaces, virtual agents, and computational systems for interactive data collection - Distributed infrastructures of data collection - ?Total Statistical Uncertainty? frameworks for estimates derived from nonprobability datasets - Defining and describing data quality in a Big Data environment - Discussing methods to deal with threats to representativeness, including methods for mitigating coverage issues - Methods for dealing with variable specification inconsistencies across datasets - Methods for repairing or mitigating missing data and data sparseness - Addressing issues in population modelling and inference - Inferential paradigms in Big Data applications - Using Big Data in various ways for sampling frame development and other sampling applications - Exploratory data analysis with Big Data - Incorporating Big Data in a Bayesian framework - Methods for --- selecting relevant data streams; --- ensuring reproducibility, traceability, and provenance; --- using Big Data to reduce, control, and evaluate total survey error; and --- evaluating quality in Big Data applications. - Handling confidentiality and privacy - Addressing legal and proprietary issues, as well as ethical concerns and the concept of harm ++++++++++++++++ Submissions ++++++++++++++++ Please submit your abstract (500 words or fewer) to https://www.bigsurv18.org/conference by February 28, 2018. Your submission should include the title of the paper, all co-authors and their affiliations, and e-mail address of the lead author. In addition, please remember to indicate your publication preference. The author of each accepted paper will present it at the conference. Presenters accepted for the edited conference volume must submit a complete version of the paper by the end of 2018. Presenters accepted for consideration in the special issue must submit a complete version of the paper for peer-review by the end of July 2018. A formal paper will not be required of presenters who do not wish to publish in either outlet. Current graduate students or recent graduates (2017 or 2018 only) are encouraged to apply for the student paper award. The authors of the two winning papers receive a Euro 150 award and a travel stipend of Euro 1,400 if traveling from outside of Europe and Euro 800 if traveling from within Europe. For details please visit https://www.bigsurv18.org/abstracts We also are interested in supporting early career scholars (graduate students or graduation date in 2017 or 2018) from all parts of the world and have established a travel award fund for this purpose. These travel awards include a travel stipend of Euro 1,400 if traveling from outside of Europe and Euro 800 if traveling from within Europe. Early career scholars from underrepresented regions are especially encouraged to apply. For details, please visit https://www.bigsurv18.org/abstracts Questions about BigSurv18 can be directed to Antje Kirchner (akirchner at rti.org ) or Craig Hill (chill at rti.org ). Conference Scientific Committee Dr. Craig Hill (Chair, editorial committee): Senior Vice President, Survey, Computing, and Statistical Sciences, RTI International, USA Dr. Antje Kirchner (Chair, organizing committee): Research Survey Methodologist, RTI International; Adjunct Research Assistant Professor, University of Nebraska?Lincoln, USA Dr. Paul Biemer: Distinguished Fellow, RTI International; Associate Director for Survey Research, Odum Institute for Research in Social Science, University of North Carolina at Chapel Hill, USA Dr. Trent Buskirk: Director, Center for Survey Research, and Professor, Department of Management Science and Information Systems, University of Massachusetts Boston, USA Dr. Ana Luc?a C?rdova Cazar: Assistant Professor, Political Science and International Relations, Universidad San Francisco de Quito, Ecuador; Adjunct Research Assistant Professor, University of Nebraska?Lincoln, USA Dr. Adam Eck: Assistant Professor, Computer Science, Oberlin College, USA Dr. Lilli Japec: Senior Scientific Advisor, Statistics Sweden, Sweden Dr. Stas Kolenikov: Senior Scientist, Abt Associates, USA Dr. Lars Lyberg: Inizio, Sweden Dr. Patrick Sturgis: Professor of Research Methodology, Department of Social Statistics and Demography, and Director of National Centre for Research Methods, University of Southampton, UK -------------- next part -------------- An HTML attachment was scrubbed... URL: From zakia_hammal at yahoo.fr Thu Nov 2 11:40:29 2017 From: zakia_hammal at yahoo.fr (zakia hammal) Date: Thu, 2 Nov 2017 15:40:29 +0000 (UTC) Subject: Connectionists: CFP: FGAHI@FG 2018, 1st International Workshop on Face and Gesture Analysis for Health Informatics References: <1836561551.1911747.1509637229186.ref@mail.yahoo.com> Message-ID: <1836561551.1911747.1509637229186@mail.yahoo.com> Apologies for cross-posting *********************************************************************************** FGAHI 2017: CALL FOR PAPERS 1st International Workshop on Face and Gesture Analysis for Health Informatics http://fgahi.isir.upmc.fr Submission Deadline: January 28th, 2018 *********************************************************************************** The 1st International Workshop on Face and Gesture Analysis for Health Informatics (FGAHI 2018) will be held in conjunction with IEEE FG 2018 on May 15-19, 2018, Xi?an, China ? https://fg2018.cse.sc.edu/ For details concerning the workshop program, paper submission, and guidelines please visit our workshop website at: http://fgahi.isir.upmc.fr Best regards, Zakia Hammal Organizing committee Kevin Bailly, Liming Chen, Mohamed Daoudi, Arnaud Dapogny, Zakia Hammal, and Di Huang Zakia Hammal, PhD The Robotics Institute, Carnegie Mellon University http://www.ri.cmu.edu/ http://ri.cmu.edu/personal-pages/ZakiaHammal/ From luca.oneto at unige.it Thu Nov 2 12:06:21 2017 From: luca.oneto at unige.it (Luca Oneto) Date: Thu, 2 Nov 2017 17:06:21 +0100 Subject: Connectionists: ESANN 2018 SS 3rd CPF - Emerging trends in machine learning: beyond conventional methods and data Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Emerging trends in machine learning: beyond conventional methods and data" at ESANN 2018 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). 25-27 April 2018, Bruges, Belgium - http://www.esann.org DESCRIPTION: Recently, new promising theoretical results, techniques, and methodologies have attracted the attention of many researchers and have allowed to broaden the range of applications in which machine learning can be effectively applied in order to extract useful and actionable information from the huge amount of heterogeneous data produced everyday by an increasingly digital world. Examples of these methods and problems are: - Learning under privacy and anonymity constraints - Learning from structured, semi-structured, multi-modal (heterogeneous) data - Constructive machine learning, e.g. generative models and structured output learning - Reliable machine learning - Learning to learn, e.g. lifelong learning and learning the loss - Mixing deep and structured learning, e.g. mixture of wide and deep models - Semantics-enabled recommender systems - Reproducibility and interpretability in machine learning - Human in the loop - Adversarial learning The focus of this special session is to attract both solid contributions or preliminary results which show the potentiality and the limitations of new ideas, refinements, or contaminations between the different fields of machine learning and other fields of research in solving real world problems. Both theoretical and practical results are welcome to our special session. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided in https://www.elen.ucl.ac.be/esann /index.php?pg=submission. Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Submission of papers: 20 November 2017 Notification of acceptance: 31 January 2018 ESANN conference: 25-27 April 2018 SPECIAL SESSION ORGANISERS Luca Oneto , University of Genoa (Italy) Nicol? Navarin , University of Padua (Italy) Michele Donini , Istituto Italiano di Tecnologia (Italy) Davide Anguita , University of Genoa (Italy) ------------------------------------------------------------ ----------------------- Luca Oneto, PhD University of Genoa web: www.lucaoneto.com DIBRIS Department e-mail: Luca.Oneto at unige.it SmartLab Laboratory e-mail: Luca.Oneto at gmail.com Via Opera Pia 11a Fax: +39-010-3532897 <+39%20010%20353%202897> 16145 Genoa ITALY Phone: +39-010-3532192 <+39%20010%20353%202192> www.smartlab.ws ------------------------------------------------------------ ----------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.eppler at fz-juelich.de Fri Nov 3 06:50:50 2017 From: j.eppler at fz-juelich.de (Jochen Martin Eppler) Date: Fri, 3 Nov 2017 11:50:50 +0100 Subject: Connectionists: Release of NEST 2.14.0 Message-ID: <54cf7ccf-0805-853b-53eb-deefa33f5c26@fz-juelich.de> Dear NEST users, it is our great pleasure to announce the release of NEST 2.14.0! The release contains 705 repository commits by 33 contributors from all across the globe. It brings many bug fixes and improvements, most notably a framework for the simulation of rate based neuron models. For a full list of changes and download links, see https://github.com/nest/nest-simulator/releases/tag/v2.14.0 All users are encouraged to upgrade as soon as possible to benefit from the improvements in the new version. Best regards, Jochen Eppler & Dennis Terhorst! -- Dr. Jochen Martin Eppler Phone: +49(2461)61-96653 ---------------------------------- Simulation Laboratory Neuroscience J?lich Supercomputing Centre Institute for Advanced Simulation ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ From julia.vogt at unibas.ch Fri Nov 3 12:12:00 2017 From: julia.vogt at unibas.ch (Julia Vogt) Date: Fri, 3 Nov 2017 16:12:00 +0000 Subject: Connectionists: Fully-funded PhD position in machine learning / computational medicine at University of Basel (Switzerland) Message-ID: <36376D4EC14B284188D4B2E85E7D625EDE0614@urz-mbx-4.urz.unibas.ch> Fully-funded PhD position in machine learning / computational medicine at University of Basel (Switzerland) Candidates with a strong interest in computational medicine and machine learning are invited to apply for a PhD position at the Department of Mathematics and Computer Science at the University of Basel. General Information. The main focus of the newly formed Adaptive Systems and Medical Data Science group led by Prof. Julia Vogt is on developing novel machine learning methods, tailored to precision medicine and the analysis of big clinical data. The group performs research at the boundary of computer science, biomedical data analysis, and clinical research. The aim is to advance the computational and statistical tools that are necessary to solve open problems in data-driven medicine. Prerequisites. Ideal candidates have a solid technical education (Master's degree in computer science, machine learning, statistics, applied mathematics, physics or related fields) and excellent programming skills. They have a vivid interest in medical informatics and are interested to work in an interdisciplinary research environment. Applicants should be highly motivated and have good communication skills (English). The successful candidate is expected to join collaborative projects at the interface between computational medicine and machine learning. Starting date: January 1st, 2018. Successful candidates will be awarded a fellowship with a competitive salary. Applications with a full CV, short statement of research interests and names of at least one referee should be submitted in electronic form to: julia.vogt at unibas.ch =============================== Prof. Dr. Julia Vogt Department of Mathematics and Computer Science University of Basel Spiegelgasse. 1, CH-4051 Basel, Switzerland email: julia.vogt at unibas.ch =============================== -------------- next part -------------- An HTML attachment was scrubbed... URL: From steve at bu.edu Sat Nov 4 09:26:11 2017 From: steve at bu.edu (Stephen Grossberg) Date: Sat, 4 Nov 2017 09:26:11 -0400 Subject: Connectionists: from normal learning and recognition to Alzheimer's disease Message-ID: Dear Colleagues, I am writing to call your attention to the following article because the neural model that it describes links normal category learning and recognition to clinical disorders such as autism and Alzheimer?s disease, topics that are currently of great interest and concern. The clinical links emerged after the neural dynamics of vigilance control during normal category learning was sufficiently understood. Grossberg, S. (2017). Acetylcholine neuromodulation in normal and abnormal learning and memory: Vigilance control in waking, sleep, autism, amnesia, and Alzheimer?s disease. Frontiers in Neural Circuits, November 2, 2017, https://doi.org/10.3389/fncir.2017.00082 Best, Steve Stephen Grossberg http://en.wikipedia.org/wiki/Stephen_Grossberg http://scholar.google.com/citations?user=3BIV70wAAAAJ&hl=en https://youtu.be/9n5AnvFur7I Wang Professor of Cognitive and Neural Systems Professor of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering Director, Center for Adaptive Systems http://cns.bu.edu/~steve steve at bu.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From michel.verleysen at uclouvain.be Sat Nov 4 16:01:33 2017 From: michel.verleysen at uclouvain.be (Michel Verleysen) Date: Sat, 4 Nov 2017 20:01:33 +0000 Subject: Connectionists: ESANN 2018 2nd call for papers Message-ID: ESANN 2018 - 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges, Belgium, 25-26-27 April 2018 http://www.esann.org/ Call for papers The call for papers is available at http://www.esann.org/. Deadline for submissions: November 20, 2017. The ESANN conferences cover machine learning, artificial neural networks, statistical information processing and computational intelligence. Mathematical foundations, algorithms and tools, and applications are covered. In addition to regular sessions, 7 special sessions will be organized on the following topics: - Deep Learning in Bioinformatics and Medicine - Machine Learning and Data Analysis in Astroinformatics - Interaction and User Integration in Machine Learning for Information Visualisation - Emerging trends in machine learning: beyond conventional methods and data - Shallow and Deep models for transfer learning and domain adaptation - Randomized Neural Networks - Impact of Biases in Big Data ESANN 2018 builds upon a successful series of conferences organized each year since 1993. ESANN has become a major scientific event in the machine learning, computational intelligence and artificial neural networks fields over the years. The conference will be organized in Bruges, one of the most beautiful medieval towns in Europe. Designated as the "Venice of the North", the city has preserved all the charms of the medieval heritage. Its centre, which is inscribed on the Unesco World Heritage list, is in itself a real open air museum. We hope to receive your submission to ESANN 2018 and to see you in Bruges next year! ======================================================== ESANN - European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning http://www.esann.org/ * For submissions of papers, reviews, registrations: Michel Verleysen Univ. Cath. de Louvain - Machine Learning Group 3, pl. du Levant - B-1348 Louvain-la-Neuve - Belgium tel: +32 10 47 25 51 - fax: + 32 10 47 25 98 mailto:esann at uclouvain.be * Conference secretariat d-side conference services 24 av. L. Mommaerts - B-1140 Evere - Belgium tel: + 32 2 730 06 11 - fax: + 32 2 730 06 00 mailto:esann at uclouvain.be ======================================================== [http://www.uclouvain.be/cps/ucl/doc/ac-arec/images/logo-signature.png] Michel Verleysen Professor ICTEAM institute Place du Levant, 3 box L5.03.02 B-1348-Louvain-la-Neuve michel.verleysen at uclouvain.be T?l. +32 10 47 25 51 - Fax +32 10 47 25 98 perso.uclouvain.be/michel.verleysen -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 3010 bytes Desc: image001.png URL: From jedlicka at em.uni-frankfurt.de Sun Nov 5 05:27:50 2017 From: jedlicka at em.uni-frankfurt.de (Peter Jedlicka) Date: Sun, 05 Nov 2017 11:27:50 +0100 Subject: Connectionists: PhD position in computational modeling of hippocampal neurons Message-ID: <20171105112750.Horde.CpzWy5ueDY9-eJf-mDuePe5@webmail.server.uni-frankfurt.de> A PhD position is available to work with Peter Jedlicka (Justus Liebig University Giessen and Goethe-University Frankfurt) in a project aimed at computational modeling of hippocampal neurons. The PhD student will be involved in the generation and implementation of computational models focusing on synaptic plasticity and excitability of hippocampal neurons. The student will be using computer models to reproduce/predict data from electrophysiology experiments and developing simulation tools contributing to 3R animal protection strategies. The successful candidate should have a background in physics, mathematics, engineering, computational neuroscience, computational biology or a related field. Experience in scientific programming is necessary. Experience with compartmental modeling is a plus. The project includes morphological modeling in close collaboration with Dr. Hermann Cuntz (FIAS and Ernst-Str?ngmann Institute, Frankfurt). The successful candidate will also collaborate with experimental and computational labs in Giessen and Frankfurt. Please submit your application, CV and statement of research interests to: Prof. Dr. Peter Jedlicka (Peter.Jedlicka at informatik.med.uni-giessen.de) Computer-Based Modeling in the field of 3R Animal Protection, Faculty of Medicine, Justus-Liebig-University, Giessen The project is related to these recent publications: Platschek S, Cuntz H, Vuksic M, Deller T, Jedlicka P. A general homeostatic principle following lesion induced dendritic remodeling. Acta Neuropathol Commun., 4:19 2016 Jedlicka P, Benuskova L, Abraham WC. A Voltage-Based STDP Rule Combined with Fast BCM-Like Metaplasticity Accounts for LTP and Concurrent "Heterosynaptic" LTD in the Dentate Gyrus In Vivo. PLoS Comput Biol. 11(11):e1004588, 2015 Beining M, Jungenitz T, Radic T, Deller T, Cuntz H, Jedlicka P, Schwarzacher SW. Adult-born dentate granule cells show a critical period of dendritic reorganization and are distinct from developmentally born cells. Brain Struct Funct. 222:1427-1446, 2017 -- Peter Jedlicka, MD, PhD Professorship for Computer-Based Modelling in the field of 3R Animal Protection Faculty of Medicine Justus-Liebig-University Rudolf-Buchheim-Str. 6 D-35392 Giessen Phone: ++49 (0)69 179 238 6269 Fax: ++49 (0)641 9941359 NeuroScience Center Clinical Neuroanatomy (Anatomy I) Goethe-University Theodor-Stern-Kai 7 D-60590 Frankfurt am Main Fax: ++49 (69) 6301 6425 Email: jedlicka at em.uni-frankfurt.de From annecollins at berkeley.edu Sun Nov 5 11:42:04 2017 From: annecollins at berkeley.edu (Anne Collins) Date: Sun, 5 Nov 2017 08:42:04 -0800 Subject: Connectionists: Open Rank position in Computational Cognitive Science at UC Berkeley Message-ID: The Department of Psychology and the Cognitive Science Program seek to fill an open-rank, tenure-track or tenured position in the area of computational cognitive science, with an anticipated start date of July 1, 2018. The position is advertised at ? Science Careers (Science magazine's online job posting site) ? Nature (naturejobs.com) and other job listings. Please see the attached job description. Best, Anne Collins ? CogSci_Ad_Description-Updated_10.27.17.pdf ? -- Anne Collins Assistant Professor Tolman Hall, 3429 Department of Psychology University of California, Berkeley (510) 664-7146 -------------- next part -------------- An HTML attachment was scrubbed... URL: From cristian.sminchisescu at math.lth.se Sun Nov 5 03:14:33 2017 From: cristian.sminchisescu at math.lth.se (Cristian Sminchisescu) Date: Sun, 5 Nov 2017 09:14:33 +0100 Subject: Connectionists: postdoc/research scientist positions, machine learning and/or computer vision, Lund University Message-ID: Dear Colleague, Would you be so kind to post this announcement on the Connectionists mailing list? Many thanks, Cristian ========================================================================= Post-doctoral/Research Scientist positions at Lund University, with focus on Computer Vision and/or Machine Learning (deadline 21.Nov.2017, 11:59 PM CET) == Topic: Several positions are available in the area of computer vision and/or machine learning, with applications to scene understanding (semantic segmentation, 3d reconstruction, object modeling, active object and action recognition, and image categorization) from images and video data. These positions are funded in part under the European Research Council Consolidator grant SEED. Funding is available for a period of up to 2 years and can be renewed to a maximum of 4 years. The research aims to design generally applicable methods for visual feature extraction based on hierarchical, deep architectures as well as large-scale numerical optimization and machine learning techniques generally applicable to perceptual data. Depending on the interest and strengths of the candidate the work can focus on one (or several) of the following aspects: numerical optimization and machine learning algorithms including deep learning and reinforcement learning, statistical models, 2d or 3d modeling, hierarchical feature extraction, computational visual attention mechanisms, semantic segmentation, object recognition and image categorization. The approach is strongly research oriented, targeting contributions in high-profile international journals and conferences in computer vision, machine learning, computer graphics or automatic control. We focus on novel theoretical and algorithmic contributions, but also the design of associated proof-of concept prototypes. == Work duties: The successful candidates will be involved in research along one of the above themes in collaboration with Prof. Cristian Sminchisescu and his group members. The main duties involved in a post-doctoral position is to conduct research. Teaching may also be included (depending on the interest of the candidate), but up to no more than 20% of working hours. The position shall include the opportunity for three weeks of training in higher education teaching and learning. == Qualification requirements: Appointment to a post-doctoral/research scientist position requires that the applicant has a PhD, or an international degree deemed equivalent to a PhD, within the subject of the position, completed no more than three years before the last date for applications. Under special circumstances, the doctoral degree can have been completed earlier. Additional requirements: Very good oral and written proficiency in English. Strong mathematical background, familiarity with scientific programming environments (Matlab, TensorFlow, Caffee) as well as programming languages C/C++/Python. Applicants for a Postdoc/Research Scientist position must have at least one publication at major computer vision or machine learning top-level international conference of journal including ICCV, CVPR, ECCV, ICLR, ICML, NIPS, PAMI, IJCV, JMLR. This is a career development position primarily focused on research. The position is intended as an initial step in a career, and the assessment of the applicants will primarily be based on their research qualifications and potential as researchers. Particular emphasis will be placed on research skills within the subject. == Application deadline: 21.Nov.2017 11:59 PM CET == Please apply formally using Lund University?s job application system: https://lu.mynetworkglobal.com/en/what:job/jobID:174474/ type:job/where:4/apply:1 -------------- next part -------------- An HTML attachment was scrubbed... URL: From cdiekman at gmail.com Mon Nov 6 11:14:56 2017 From: cdiekman at gmail.com (Casey Diekman) Date: Mon, 6 Nov 2017 11:14:56 -0500 Subject: Connectionists: Faculty position in Math Biology at NJIT Message-ID: The Department of Mathematical Sciences (DMS) at New Jersey Institute of Technology (NJIT) invites applications for a tenure-track position at the assistant professor level in mathematical biology. A second DMS tenure-track assistant professor position in the broader area of applied mathematics is advertised separately (links provided below). The appointment is to start in Fall 2018. Candidates should have a Ph.D. in mathematics, applied mathematics or a related discipline, with an established record of independent research, strong potential for seeking external research support, and a commitment to teaching at graduate and undergraduate levels. Candidates working in any subfield of mathematical biology will be given consideration. Currently, members of the DMS mathematical biology group are engaged in research in computational neuroscience, biological rhythms, biofluids and mechanosensing. To apply, please visit https://njit.csod.com/ats/careersite/JobDetails.aspx?site=1&id=35. The second position in applied mathematics is advertised separately at: https://njit.csod.com/ats/careersite/JobDetails.aspx?site=1&id=30. Submissions must include (a) cover letter, (b) resume/CV, (c) research statement, (d) teaching statement, and (e) names and contact information for at least four references. Review of applications will begin immediately and will continue until the position is filled. Please direct any questions to the search committee chair, Victor Matveev, at matveev at njit.edu. DMS is recognized for its strong program in applied mathematics, which offers B.S., M.S., and Ph.D. degrees, with Ph.D. program tracks in applied mathematics as well as in applied probability and statistics. NJIT is in the University Heights neighborhood next to vibrant downtown Newark, about 12 miles west of New York City. The NJIT campus is adjacent to the campus of Rutgers-Newark, with which it shares several academic programs. DMS has close collaborative ties to the Department of Biological Sciences at NJIT. Excellent potential for outside collaboration is also afforded by the close geographic proximity of NJIT to other prominent centers for biological research such as the Center for Molecular and Behavioral Neuroscience at Rutgers-Newark, New Jersey Medical School, NYU, Columbia University, and Rockefeller University. Apart from mathematical biology, DMS faculty work in diverse fields of applied mathematics including fluid dynamics, granular matter, nonlinear waves, applied analysis, scientific computing, dynamical systems, and probability and statistics. NJIT is an Equal Opportunity / Affirmative Action Employer and encourages women, minorities, persons with disabilities and Vietnam era and disabled veterans to apply. ___________________________________ Victor Matveev, Professor Applied Math, Biophysics & Neuroscience Department of Mathematical Sciences Graduate Faculty, Dept of Biological Sciences New Jersey Institute of Technology Newark, NJ 07102-1982 Office: Cullimore Hall 616 E-mail: matveev at njit.edu http://web.njit.edu/~matveev/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephan.busemann at dfki.de Mon Nov 6 11:37:37 2017 From: stephan.busemann at dfki.de (Stephan Busemann) Date: Mon, 6 Nov 2017 17:37:37 +0100 Subject: Connectionists: Researcher in Machine Learning for NLP with a Focus on Deep Learning and, Machine Translation, DFKI, Germany Message-ID: <583e5f84-085c-90f6-52d0-255ffcea8dbe@dfki.de> [Apologies for crossposting]* Researcher in Machine Learning for NLP with a Focus on Deep Learning and ** **Machine Translation, DFKI, Germany * The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning for NLP with a focus on Deep Learning and Machine Translation. Depending on track record and experience, the position is available at the Junior/Researcher/Senior level. / //Research responsibilities include: / - machine learning and deep learning for machine translation - publication in top-tier conferences and journals - software development and integration /General responsibilities include:/ - basic research as well as industry funded applied research - identification of funding opportunities and engagement in proposal writing - contribution to teaching and supervision in accordance with University and ? DFKI rules and regulations - administrative work associated with programmes of research /Requirements: / - MSc/PhD in computer science, machine learning, natural language processing, ? computational linguistics or similar - Strong background and track record in machine learning and deep learning as ? well as in MT and NLP - Strong problem solving and programming skills, independent and creative ? thinking - Strong team working and communication skills, as well as excellent command ? of written and oral English. Command of German or other languages will be? helpful, but is not a requirement. Successful applicants will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University). /Starting date, duration, salary: / Preferred starting dates are early Spring 2018.? The position is available for a duration of three years, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills. /Application: / Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) and inquiries to mlt-sek at dfki.de referring to job opening no. 97/17/JvG. Deadline for applications is November 30th, 2017. The position remains open until filled. Please contact josef.van_genabith at dfki.de for informal inquiries. -- Prof.Dr. Stephan Busemann, Principal Researcher Associate Head of Language Technology Department DFKI GmbH, Stuhlsatzenhausweg 3, D-66123 Saarbruecken phone: (+49 681) 85775-5286, fax: (+49 681) 85775-5338 http://www.dfki.de/~busemann ------------------------------------------------------------- Deutsches Forschungszentrum fuer Kuenstliche Intelligenz GmbH Trippstadter Strasse 122, D-67663 Kaiserslautern, Germany Geschaeftsfuehrung: Prof. Dr. Dr. h.c. mult. Wolfgang Wahlster (Vorsitzender) Dr. Walter Olthoff Vorsitzender des Aufsichtsrats: Prof. Dr. h.c. Hans A. Aukes Amtsgericht Kaiserslautern, HRB 2313 ------------------------------------------------------------- -- Prof.Dr. Stephan Busemann, Principal Researcher Associate Head of Language Technology Department DFKI GmbH, Stuhlsatzenhausweg 3, D-66123 Saarbruecken phone: (+49 681) 85775-5286, fax: (+49 681) 85775-5338 http://www.dfki.de/~busemann ------------------------------------------------------------- Deutsches Forschungszentrum fuer Kuenstliche Intelligenz GmbH Trippstadter Strasse 122, D-67663 Kaiserslautern, Germany Geschaeftsfuehrung: Prof. Dr. Dr. h.c. mult. Wolfgang Wahlster (Vorsitzender) Dr. Walter Olthoff Vorsitzender des Aufsichtsrats: Prof. Dr. h.c. Hans A. Aukes Amtsgericht Kaiserslautern, HRB 2313 ------------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From erdi.peter at wigner.mta.hu Mon Nov 6 17:39:50 2017 From: erdi.peter at wigner.mta.hu (=?ISO-8859-2?Q?=C9rdi_P=E9ter?=) Date: Mon, 6 Nov 2017 23:39:50 +0100 (CET) Subject: Connectionists: aboutranking.com Message-ID: My Dear Collegaues: I have a website/blog aboutranking.com . about the topic, (possibly a book) RANKING. The reality, illusion and manipulation of objectivity If you find relevant/interseting for you, please push the "Follow" button rightdown, and make comments and suggestions! Any advice is highly appreciated. *** Like it or not, ranking is with us. We like ranking because it is simple and objective, and dislike because it is biased and subjective. RANKING discusses the Hows and Whys of our love and fear of rankings and being ranked through real life examples examined from three different angles (reality, illusion, and manipulation) of objectivity. Ranking converts scientific theories to everyday experiences by raising and answering questions as: are college ranking lists objective? How to rank and rate countries based on their fragility, corruption or even happiness? How to find the most relevant web pages? How to rank employees? How to improve our digital reputation? We should find strategies how to navigate between objective and subjective evaluations and gets help to identify and modify our place in real and virtual communities by combining our human intelligence with computational techniques. ***** Kind regards, Peter Erdi http://people.kzoo.edu/~perdi/ From tomas.hromadka at gmail.com Mon Nov 6 18:16:22 2017 From: tomas.hromadka at gmail.com (Tomas Hromadka) Date: Tue, 7 Nov 2017 00:16:22 +0100 Subject: Connectionists: COSYNE 2018: Abstract submission closes soon, Registration, Travel grants Message-ID: <557c3581-131d-5e68-e2ac-525470bc55fa@gmail.com> ==================================================== Computational and Systems Neuroscience 2018 (Cosyne) MAIN MEETING 01 - 04 March 2018 Denver, Colorado WORKSHOPS 05 - 06 March 2018 Breckenridge, Colorado www.cosyne.org ==================================================== IMPORTANT DATES Abstract submission is now open. *Abstract submission deadline: 20 November 2017* Online registration opens: 10 November 2017 Travel grant submission opens: 10 November 2017 ---------------------------------------------------- COSYNE ---------------------------------------------------- The annual Cosyne meeting provides an inclusive forum for the exchange of empirical and theoretical approaches to problems in systems neuroscience, in order to understand how neural systems function. The MAIN MEETING is single-track. A set of invited talks is selected by the Executive Committee, and additional talks and posters are selected by the Program Committee, based on submitted abstracts. The WORKSHOPS feature in-depth discussion of current topics of interest, in a small group setting. For details on workshop proposals please see below or visit Cosyne.org -> Workshops. Cosyne topics include but are not limited to: neural coding, natural scene statistics, dendritic computation, neural basis of persistent activity, nonlinear receptive field mapping, representations of time and sequence, reward systems, decision-making, synaptic plasticity, map formation and plasticity, population coding, attention, and computation with spiking networks. This year we would like to foster increased participation from experimental groups as well as computational ones. Please circulate widely and encourage your students and postdocs to apply. When preparing an abstract, authors should be aware that not all abstracts can be accepted for the meeting, due to space constraints. Abstracts will be selected based on the clarity with which they convey the substance, significance, and originality of the work to be presented. For more information and details on submitting abstracts please visit Cosyne.org -> Abstracts. ----------------------------------------------- TRAVEL GRANTS ----------------------------------------------- Applications are now open for travel grants to attend the conference. Each awardee will receive at least $500 to help offset the costs of travel, registration, and accommodations. Larger grants may be available to those traveling from outside North America. Special consideration is given to scientists who have not previously attended the meeting, under-represented minorities, students who are attending the meeting together with a mentor, undergraduate students, and authors of submitted Cosyne abstracts. We currently offer four travel grant programs for New Attendees, Presenters, Mentors, and Undergraduates. For details on applying, see Cosyne.org -> Travel grants. COSYNE SPEAKERS Tim Behrens (Oxford) Josh Berke (UCSF) Tiago Branco (UCL) Jessica Cardin (Yale) Claudia Clopath (Imperial) Marlene Cohen (Pittsburgh) Iain Couzin (Max-Planck) Carina Curto (Penn State) Ann Graybiel (MIT) Vivek Jayaraman (Janelia) Mate Lengyel (Cambridge) Joni Wallis (Berkeley) Byron Yu (CMU) ORGANIZING COMMITTEE General Chairs: Ilana Witten (Princeton) and Eric Shea-Brown (U Washington) Program Chairs: Linda Wilbrecht (Berkeley) and Brent Doiron (U Pittsburgh) Workshop Chairs: Laura Busse (LMU) and Ralf Haefner (U Rochester) Undergraduate Travel Chairs: Angela Langdon (Princeton) and Robert Wilson (U Arizona) Publicity Chair: Il Memming Park (Stony Brook) Development Chair: Michael Long (NYU) EXECUTIVE COMMITTEE Stephanie Palmer (U Chicago) Zachary Mainen (Champalimaud) Alexandre Pouget (U Geneva) Anthony Zador (CSHL) CONTACT meeting [at] cosyne.org COSYNE MAILING LISTS Please consider adding yourself to Cosyne mailing lists (groups) to receive email updates with various Cosyne-related information and join in helpful discussions. See Cosyne.org -> Mailing lists for details. From hava.siegelmann at gmail.com Tue Nov 7 10:04:49 2017 From: hava.siegelmann at gmail.com (Hava Siegelmann) Date: Tue, 7 Nov 2017 10:04:49 -0500 Subject: Connectionists: Hiring for Lifelong Learning Machines Message-ID: Dear friends and colleagues, Lifelong Learning Machines team selected the researchers, and preparing the kick-off meeting. At this stage we are looking to hire a researcher that has great interest and talent in this topic as well a some managerial and people skills to join the team supporting the L2M programs. Please contact me directly with CV, statement of interest, and 3 recommenders. With regards Hava Siegelmann -------------- next part -------------- An HTML attachment was scrubbed... URL: From a.stein at fz-juelich.de Tue Nov 7 10:06:42 2017 From: a.stein at fz-juelich.de (Alexandra Stein) Date: Tue, 7 Nov 2017 16:06:42 +0100 Subject: Connectionists: SfN 2017: Visit the Bernstein Network Computational Neuroscience at booth #3523 Message-ID: <03648ac3-1e1d-9528-d6e9-7e6cb3f24051@fz-juelich.de> Dear all, The Bernstein Network Computational Neuroscience [6] will be an exhibitor at the SfN Meeting 2017. Please find us at the NEUROSCIENCE IN GERMANY booth #3523. The Bernstein Network will present: * research fields * study and training programs * open positions * research and funding opportunities * infrastructural facilities Furthermore, the German Neuroinformatics Node (G-Node) [7] will present their data management services [8] for organizing, sharing, and publishing research data. Demo presentations times are: Monday, Tuesday, Wednesday (Nov 13, 14, 15) 3pm - 5pm, or by individual appointment (mail to info at g-node.org). We are looking forward to welcoming you at booth #3523! Best regards Alexandra Stein -- Dr. Alexandra Stein Head of Bernstein Coordination Site Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum J?lich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9583 mobile: (+49) 0151 67114645 mail: a.stein at fz-juelich.de web: www.nncn.de Twitter: NNCN_Germany YouTube: Bernstein TV Facebook: Bernstein Network Computational Neuroscience, Germany LinkedIn: Bernstein Network Computational Neuroscience, Germany ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From james.rankin at gmail.com Tue Nov 7 12:12:32 2017 From: james.rankin at gmail.com (James Rankin) Date: Tue, 7 Nov 2017 17:12:32 +0000 Subject: Connectionists: EPSRC funded PhD in Computational/Mathematical Neuroscience (funded for UK students) Message-ID: *3 EPSRC funded PhD positions in Computational & Mathematical Neuroscience* UK students (or students who have spent last 3 years in UK) fully funded (fees and stipend) EU students partially funded (fees but no stipend) International students not eligible Application deadline: 10th January 2018 The studentships will provide funding for a stipend which is currently ?14,553 per annum for 2017-2018. It will provide research costs and UK/EU tuition fees at Research Council UK rates for 42 months (3.5 years) for full-time students, pro rata for part-time students. * The neural circuitry mediating multisensory integration in Platynereis larvae* Supervisors: Dr James Rankin and Prof G?sp?r J?kely (Living Systems Institute, Exeter) http://www.exeter.ac.uk/studying/funding/award/?id=2901 * Cortical network models to understand differential input response properties during active and silent states* Supervisors: Dr James Rankin and Dr Mick Craig (Medical School, Exeter) http://www.exeter.ac.uk/studying/funding/award/?id=2903 * Determination of parameter dependencies across diverse populations of neuronal and excitable cells* Supervisors: Dr James Rankin and Dr Joel Tabak (Medical School, Exeter) http://www.exeter.ac.uk/studying/funding/award/?id=2932 Apply through links above or contact pgrenquiries at exeter.ac.uk or j.a.rankin at exeter.ac.uk directly with any questions. -- http://emps.exeter.ac.uk/mathematics/staff/jar226 -------------- next part -------------- An HTML attachment was scrubbed... URL: From bengioy at iro.umontreal.ca Tue Nov 7 13:02:59 2017 From: bengioy at iro.umontreal.ca (bengioy at iro.umontreal.ca) Date: Tue, 7 Nov 2017 13:02:59 -0500 Subject: Connectionists: faculty positions at U. Montreal on neural networks Message-ID: Hello, My department (CS and OR @ U. Montreal) and my institute (MILA) are seeking applications for two full-time tenure-track positions, one at the rank of Assistant Professor or Associate Professor, and one at the rank of Assistant Professor, in areas related to machine learning, neural networks and their applications (e.g., natural language processing, computer vision, robotics). Deep learning is an obvious asset given the concentration we already have there. See information on the MILA page below. Come and join the world's fastest growing AI hub in Montreal! The deadline for the CS department applications at MILA-U. Montreal is Dec. 1st, just a few weeks away. These are very likely to come with a generous and prestigious CIFAR AI Chair. Although these are two positions in the CS department, we will also open a position for candidates to a CIFAR AI Chair outside of the CS department (such as math, stats, cognitive neuroscience, cognitive psychology or possibly physics). For such non-CS candidates, contact me directly. https://mila.quebec/en/2017/09/professor-in-machine-learning/ -- Yoshua Bengio From barrow at morganclaypool.com Tue Nov 7 13:21:54 2017 From: barrow at morganclaypool.com (Bebe Barrow) Date: Tue, 7 Nov 2017 10:21:54 -0800 Subject: Connectionists: Morgan & Claypool Announces First Comprehensive, Technical Autonomous Vehicles Book Message-ID: <010801d357f5$4a5513d0$deff3b70$@morganclaypool.com> Creating Autonomous Vehicle Systems Shaoshan Liu, PerceptIn Liyun Li, Baidu US Jie Tang, South China University of Technology Shuang Wu, YiTu Jean-Luc Gaudiot, University of California, Irvine Paperback ISBN: 9781681730073 eBook ISBN: 9781681730080 October 2017, 196 pages Morgan & Claypool Publishers is proud to announce the publication of the first technical book on autonomous vehicles for a general computer science audience. Creating Autonomous Vehicle Systems is written by four leading research and development experts in the field and provides both underlying theory and practical applications for this fast-growing technology area. http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?produc ts_id=1090 This book will be useful to hardware and software engineers, students, and autonomous vehicle researchers and practitioners. Students interested in autonomous driving will find this a comprehensive overview of the entire autonomous vehicle technology stack. Researchers will find plenty of references for an effective, deeper exploration of the various technologies, and practitioners will find many practical techniques used successfully by the authors. Autonomous driving is not one single technology; it is an integration of many technologies. It demands innovations in algorithms, system integrations, and cloud platforms. Creating Autonomous Vehicle Systems covers each of these subsystems in detail: algorithms for localization, perception, and planning and control; client systems, such as the robotics operating system and hardware platform; and the cloud platform, which includes data storage, simulation, high-definition (HD) mapping, and deep learning model training. Review copies (eBook) are available for academic and professional courses as well as for media. Please contact Brent Beckley (beckley at morganclaypool.com ) -- Bebe Barrow Sales & Marketing Assistant Morgan & Claypool Publishers barrow at morganclaypool.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.biehl at rug.nl Wed Nov 8 03:59:50 2017 From: m.biehl at rug.nl (Michael Biehl) Date: Wed, 8 Nov 2017 10:59:50 +0200 Subject: Connectionists: Fwd: CFP: Special Session at ESANN 2018 In-Reply-To: References: Message-ID: Apologies for cross-posting SECOND CALL FOR PAPERS *Special Session at ESANN 2018* 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges/Belgium, April 25-27 2017. *Machine Learning and Data Analysis in Astroinformatics* *Organized by M. Biehl, K. Bunte (University of Groningen, The Netherlands), **G. Longo (University of Naples, Italy), P. Tino (University of Birmingham, UK) * The ever-growing amount of data which becomes available in many domains clearly requires the development of efficient methods for data mining and analysis. These challenges occur in a variety of areas including societal issues, business and fundamental scientific research. Astronomy continuous to be at the forefront of this development: Modern observational techniques provide enormous amounts of data, which have to be processed efficiently. The development of methods for their reliable acquisition and analysis has immediate impact on other areas including commercial applications, data security, environmental monitoring etc. This special session is meant to attract researchers who develop, investigate or apply methods of neural networks, machine learning and data analysis in the context of astronomical data. Potential topics include, but are not limited to - big data mining in astronomy - the processing of astronomical images - filtering techniques for streams of astronomical data - outlier and novelty detection in observational data - classification or clustering of celestial objects - simulation of astrophysical models and related - inference problems - the analysis of heterogeneous data stemming from - various sources or technical platforms Important dates: Submission of papers: 20 November 2017 Notification of acceptance: 31 January 2018 ESANN conference: 25 - 27 April 2018 More information can be found at http://www.elen.ucl.ac.be/esann/index.php?pg=specsess#astroinformatics http ://www.esann.org -- ---------------------------------------------------------- Prof. Dr. Michael Biehl Johann Bernoulli Institute for Mathematics and Computer Science P.O. Box 407, 9700 AK Groningen The Netherlands Tel. +31 50 363 3997 www.cs.rug.nl/~biehl m.biehl at rug.nl -------------- next part -------------- An HTML attachment was scrubbed... URL: From avellido at lsi.upc.edu Wed Nov 8 10:49:39 2017 From: avellido at lsi.upc.edu (Alfredo Vellido) Date: Wed, 8 Nov 2017 16:49:39 +0100 Subject: Connectionists: ESANN'18: 2nd CFP: Sp.Sess. on DEEP LEARNING in BIOINFORMATICS and MEDICINE Message-ID: <2dd6ceb4-686c-de75-ceb2-28fed4fe0592@lsi.upc.edu> ***Apologies for crossposting*** 2nd CFP:? special session on "DEEP LEARNING in BIOINFORMATICS and MEDICINE" at ESANN 2018 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. 25-27 April 2018, Bruges, Belgium www.esann.org DESCRIPTION: Deep learning (DL) has been harnessing the attention of the machine learning research community over the latter years. Much of its success roots on having made available models and technologies capable of achieving ground-breaking performances in a variety of traditional fields of application of machine learning, such as machine vision and natural language processing (NLP). Medicine, genetics, biology and chemistry are among the research fields where machine learning models find most consolidated applications. Admittedly, some of the DL flagships, like NLP and image processing have their implications in Medicine, e.g., in extracting information from the text of patients? records or in analyzing medical imagery to find anomalous patterns. However, DL methodologies have only recently started to be used to address relevant bioinformatics and cheminformatics challenges. Reasons for such a slowed-down permeation can be sought in the complexity of the DL models which might prove difficult to use in novel application fields by non-machine learning experts. Lack of interpretability and insight into the trained models might also have been a limiting factor. Despite such few limitations, DL methodologies offer far more enabling aspects and technologies for developing impacting contributions in bioinformatics research. Between the most relevant are the ability to effectively and efficiently process complex, large scale and multi-modal data, e.g. collections of biomedical images and associated patient information, DNA sequences, molecular graphs. The modular design of deep architectures together with the potential for re-using parts of previously trained models on novel tasks is another potential success enabler for bioinformatics applications. This special session is meant to attract researchers who develop, investigate, or apply DL methods on biomedical and chemistry data. We aim to bring together researchers working on the topic from both the deep learning and the bioinformatics communities. Topics include, but are not restricted to: -? DL applications and novel models for biology, chemistry, genetics, medicine and omics-data -? Interpretability and provable properties of DL models. -? Learning representations from multi-modal bioinformatics data. -? Deep models for visual analytics and inspection of biomedical data. -? NLP for knowledge discovery in the medicine field. -? Deep Reinforcement Learning for the optimization of medical treatments. -? DL for structured data processing in bioinformatics and chemistry. -? High performance computing for DL and bioinformatics. -? Software frameworks and toolkits specific for DL in bioinformatics and medical applications. SUBMISSION: Through ESANN web: http://www.elen.ucl.ac.be/esann/index.php?pg=submission. PRELIMINARY DATES: Paper submission deadline : 20 November 2017 Notification of acceptance : 31 January 2018 SPECIAL SESSION ORGANISERS: - Miguel Atencia, Universidad de M?laga (Spain) matencia at ctima.uma.es / http://www.matap.uma.es/profesor/matencia - Davide Bacciu, Universit? di Pisa (Italy) bacciu at di.unipi.it? / http://pages.di.unipi.it/bacciu - Paulo J.G. Lisboa, Liverpool John Moores University (U.K.) P.J.Lisboa at ljmu.ac.uk? / https://www.ljmu.ac.uk/about-us/staff-profiles/faculty-of-engineering-and-technology/department-of-applied-mathematics/paulo-lisboa - Jos? D. Martin, Universitat de Val?ncia (Spain) jose.d.martin at uv.es? /? http://www.uv.es/jdmg - Ruxandra Stoean, University of Craiova (Romania) rstoean at inf.ucv.ro? /? http://inf.ucv.ro/~rstoean - Alfredo Vellido, Universitat Polit?cnica de Catalunya (Spain) avellido at lsi.upc.edu? /? www.cs.upc.edu/~avellido From james.henderson at unige.ch Wed Nov 8 05:46:37 2017 From: james.henderson at unige.ch (James Henderson) Date: Wed, 8 Nov 2017 11:46:37 +0100 Subject: Connectionists: Post-doctoral position in deep learning for natural language understanding Message-ID: <41724f92-da0f-20bf-6441-21e641ce9473@unige.ch> The Idiap Research Institute seeks qualified candidates for a Postdoc position in the field of natural language understanding. The research will be conducted in the framework of EU H2020 and IARPA projects, in collaboration with international consortia. The successful candidate will work with Dr. James Henderson (http://cui.unige.ch/~hendersj/) within the Natural Language Understanding group at Idiap, and have the opportunity to collaborate with other world-class researchers in machine learning, natural language processing and speech recognition at Idiap, their project partners, and nearby EPFL.? The NLU group has expertise in representation learning and deep neural network structured prediction applied to syntactic/semantic parsing, semantic entailment, machine translation, information retrieval and other NLP tasks. The research will investigate deep learning architectures for cross-lingual natural language understanding and indexing.? The focus can include end-to-end integration with neural speech recognition, cross-lingual and compositional representation learning, low-resource training methods, machine translation, summarisation and cross-lingual information retrieval. The ideal candidate should hold a PhD degree in computer science or a related field. She/he will have a background in natural language processing and/or machine learning, with strong programming skills and an excellent publication record. Familiarity with deep learning toolkits will be an advantage. The Postdoc position is offered on a one-year basis with the possibility of renewal based on funding and performance, with a starting salary of 80,000 CHF/year.? Exceptionally qualified candidates can also be considered for a longer-term Research Associate position.? Starting date is immediate or to be negotiated. Please apply online here: http://www.idiap.ch/webapps/jobs/ors/applicant/position/index.php?PHP_APE_DR_9e581720b5ef40dc7af21c41bac4f4eb=%7B__TO%3D%27detail%27%3B__PK%3D%2710223%27%7D Sincerely, ? - James Henderson ??? james.henderson at idiap.ch From neville at cs.purdue.edu Wed Nov 8 15:22:51 2017 From: neville at cs.purdue.edu (Jennifer Neville) Date: Wed, 8 Nov 2017 15:22:51 -0500 Subject: Connectionists: Multiple Tenure-Track/Tenured Faculty Positions at Purdue (including ML) Message-ID: <389C9E23-0540-498B-AE0E-3F686016D967@cs.purdue.edu> The Department of Computer Science at Purdue University is in a phase of significant growth. Applications are being solicited for nine tenure-track and tenured positions at the Assistant, Associate and Full Professor levels. Outstanding candidates in all areas of computer science will be considered. Review of applications and candidate interviews will begin in September 2017, and will continue until the positions are filled. The Department of Computer Science offers a stimulating academic environment. Information about the department and a description of open positions are available at http://www.cs.purdue.edu. Applicants should hold a PhD in Computer Science or a related discipline, have demonstrated excellence in research, and strong commitment to teaching. Successful candidates will be expected to conduct research in their fields of expertise, teach courses in computer science, and participate in other department and university activities. Purdue University?s Department of Computer Science is committed to advancing diversity in all areas of faculty effort, including scholarship, instruction, and engagement. Candidates should address at least one of these areas in their cover letter, indicating their past experiences, current interests or activities, and/or future goals to promote a climate that values diversity, and inclusion. Salary and benefits are competitive, and Purdue is a dual-career friendly employer. Applicants are strongly encouraged to apply online at https://hiring.science.purdue.edu. Alternatively, hardcopy applications can be sent to: Faculty Search Chair, Department of Computer Science, 305 N. University Street, Purdue University, West Lafayette, IN 47907. A background check will be required for employment in this position. Purdue University is an EOE/AA employer. All individuals, including minorities, women, individuals with disabilities, and veterans are encouraged to apply. From zfalomir at gmail.com Wed Nov 8 12:32:50 2017 From: zfalomir at gmail.com (Zoe Falomir) Date: Wed, 8 Nov 2017 18:32:50 +0100 Subject: Connectionists: Special Issue on Bridging Cognitive Models and Recommender Systems (CC-CogM+RS) Message-ID: Dear Colleagues, we are launching a special issue on Bridging Cognitive Models and Recommender Systems in collaboration with "Cognitive Computation" journal at Springer. We encourage all interested researchers to submit their papers. Please let us know if you'd like to submit but are unable to meet the deadline. ================================================ Cognitive Computation Special Issue on Bridging Cognitive Models and Recommender Systems (CC-CogM+RS) Call for Papers Deadline: January 15th, 2018 ================================================ BACKGROUND: The aim of this special issue is to provide a space for researchers to discuss the possible points of contact and to highlight the issues and the advantages of bridging different fields for the study of cognitive architectures for recommendation, as well as recommender systems shaping cognitive architectures. In recent conferences and meetings, we realized that this bridged topic has not received sufficient attention. In our opinion, recommendations should also be designed/evaluated taking into account cognitive and emotional factors. This issue is closely related with key trends that are in the peak of the Gartner's 2016 Hype Cycle for Emerging Technologies ( gartner.com/newsroom/id/3412017) as cognitive expert advisors, machine learning or smart robots. This bridge should be traveled in both sides. From one side, cognition represents an ideal model to link different disciplines, as the field of Robotics and that of Interaction studies, or the field of Decision Support Systems and that of Information Retrieval. Cognitive architectures are providing recommendations to an agent (a human or a robot) in order to interact with the environment (perceived environment or collected data). On the other side, expert recommender systems, by getting assessment from collaborative human expertise, can automate, in a cognitive way, procedures and tasks, either for physical agents, like robots, or soft agents collecting information from databases or Internet. Interaction experiences bridging cognitive architectures and recommender systems refers not only to objective measures related with the associated task, but especially to the subjective ones: emotions, mood, engagement, availability. Appealing architectures managing these concerns consider fuzzy / hesitant / qualitative / uncertainty measures and reasoning. TOPICS COVERED: - Cognitive modeling, cognitive systems, cognitive architectures, cognitive representations. - Recommender systems, decision support systems, group decision making, cognitive expert advisors. - Context-aware systems, sentiment analysis, and social data analysis. - Logic and reasoning, spatial thinking, spatio-temporal reasoning, common-sense reasoning. - Theoretical foundations of cognitive models and recommender systems: machine learning, computational intelligence, data analysis and data mining, knowledge acquisition and representation, adaptive perception/cognition. - Cognitive Robotics. - Applications involving topics from above and focused on: education, robotics, creativity, ambient-intelligence, health-care SUBMISSION: Manuscripts should be prepared according to the "Instructions For Authors" of the journal found at http://www.springer.com/biomed/neuroscience/journal/12559?de tailsPage=pltci_2094392 and submissions should be done through the EditorialManager system: https://www.editorialmanager.com/cogn/default.aspx selecting the category "SI: Bridging Cognitive Models and Recommender Systems,(CC-CogM+RS)" SCHEDULING: Submissions Deadline: January 15th, 2018 First notification of acceptance: April 1st, 2018 Submission of revised papers: May 1st, 2018 Final notification to the authors: May 20th, 2018 Submission of final/camera-ready papers: June 15th, 2018 Publication of special issue: September 2018 GUEST EDITORS: - Prof. Dr. Cecilio Angulo, Universitat Polit?cnica de Catalunya - UPC BarcelonaTECH , Spain - Dr.-Ing. Zoe Falomir, Universit?t Bremen, Germany - Prof. Dr. Davide Anguita, Universit? degli Studi di Genova, Italy - Prof. N?ria Agell, ESADE - Ramon Llull University, Spain - Dr. Erik Cambria, Nanyang Technological University, Singapore FURTHER INFORMATION: For further information, please contact Zoe Falomir (zfalomir at uni-bremen dot de) Best regards, -- ------------------------------------------------------------ Dr.-Ing. Zoe Falomir Llansola https://sites.google.com/site/zfalomir/home Twitter at @zfalomir ------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From neville at cs.purdue.edu Wed Nov 8 15:22:50 2017 From: neville at cs.purdue.edu (Jennifer Neville) Date: Wed, 8 Nov 2017 15:22:50 -0500 Subject: Connectionists: Two Tenure-Track Positions in Statistics at Purdue Message-ID: <8B6C7959-7459-4F40-A15D-A21F9D6342EA@cs.purdue.edu> The Department of Statistics at Purdue University seeks to hire two tenure-track Assistant professors to begin in August 2018 in the area of data science and machine learning. Applicants with interests in novel computational and methodological approaches to complex data, as well as applicants with foundational interests in the computational theory for complex data will be considered. The Department of Statistics offers a stimulating and nurturing academic environment with research programs in a broad-range of areas, including bioinformatics, computational statistics, data science, mathematical statistics, probability, and spatial statistics. These positions will be split between the Department of Statistics (75%) and the Department of Computer Science (25%), joining other faculty with joint appointments in Computer Science or other departments. Further information about the department is available at http://www.stat.purdue.edu. All applicants should hold a Ph.D. in Statistics or a related field by the time of employment, and be committed to excellence in research and teaching. Salary and benefits are highly competitive. Please visit http://www.stat.purdue.edu/hiring/ to apply. A background check will be required for employment in this position. From 89badri at gmail.com Wed Nov 8 23:11:30 2017 From: 89badri at gmail.com (Badrinath Jayakumar) Date: Wed, 8 Nov 2017 23:11:30 -0500 Subject: Connectionists: Collecting state of the art result for all machine learning problems Message-ID: Hi all, Redditors are starting this project; they need help from everyone. " I am starting this ambitious project with the aim of collecting SoTA results for all machine learning problems and all datasets. I certainly can not do this alone. It requires support from a large community. I strongly believe r/MachineLearning can do this because ours is the largest machine learning community. URL: https://github.com/RedditSota/state-of-the-art-result-for-machine-learning-problems I need few things from you all: 1. Please often visit that GitHub page and provide SoTA results periodically. 2. Need many collaborators who can actively update the GitHub. Please PM me if you are interested. 3. In this thread, provide SoTA result for the problems you know. In need this info: * Type of learning problem * Modality * Research paper * Datasets * Metric * Source Code * Year 4. Please give visibility to this by sharing it on Facebook, Twitter, your research labs, professors, etc. If you have comments on the structure, please write to me. This is definitely possible if we work together on this" Source: https://www.reddit.com/r/MachineLearning/comments/7bqpdi/d_collecting_state_of_the_art_result_for_all/ Thanks! *Badrinath* -------------- next part -------------- An HTML attachment was scrubbed... URL: From pblouw at uwaterloo.ca Wed Nov 8 21:52:18 2017 From: pblouw at uwaterloo.ca (Peter Blouw) Date: Wed, 8 Nov 2017 21:52:18 -0500 Subject: Connectionists: Call for Applications - 2018 Nengo Summer School Message-ID: Hello! [All details about this school can be found online at https://www.nengo.ai/summerschool] The Centre for Theoretical Neuroscience at the University of Waterloo is excited to announce a special version of our annual Nengo summer school that will host the* first public access* to *Braindrop*, a new mixed analog-digital neuromorphic chip developed in collaboration with Stanford and Yale. In addition to introducing Braindrop, this two-week school will teach participants to use the Nengo simulation package to build state-of-the-art cognitive and neural models to run both in simulation and on neuromorphic hardware. Nengo provides users with a versatile and powerful environment for designing cognitive and neural systems, and has been used to build what is currently the world's largest functional brain model, Spaun [1]. Nengo is also being used to program a variety of state-of-the-art neuromorphic chips, including Braindrop! For a look at last year's summer school, check out this short video: https://goo.gl/4tVUkQ We welcome applications from all interested graduate students, research associates, postdocs, professors, and industry professionals with a relevant background. [1] Eliasmith, C., Stewart T. C., Choo X., Bekolay T., DeWolf T., Tang Y., Rasmussen, D. (2012). A large-scale model of the functioning brain. Science. Vol. 338 no. 6111 pp. 1202-1205. DOI: 10.1126/science.1225266. [ http://compneuro.uwaterloo.ca/files/publications/eliasmith.2012.pdf] Application Deadline: February 15, 2018 *Format*: A combination of tutorials and project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, modeling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, work on individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Participants will have the opportunity to learn how to: - interface Nengo with various kinds of neuromorphic hardware - build perceptual, motor, and cognitive models using spiking neurons - model anatomical, electrophysiological, cognitive, and behavioural data - use a variety of single cell models within a large-scale model - integrate machine learning methods into biologically oriented models - interface Nengo with cameras and robotic systems - implement modern nonlinear control methods in neural models - and much more... *Date and Location:* June 3th to June 15th, 2018 at the University of Waterloo, Ontario, Canada. *Applications*: Please visit http://www.nengo.ai/summerschool, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact Peter Blouw (peter.blouw at appliedbrainresearch.com). We look forward to hearing from you! -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.hausser at ucl.ac.uk Thu Nov 9 02:13:10 2017 From: m.hausser at ucl.ac.uk (Hausser, Michael) Date: Thu, 9 Nov 2017 07:13:10 +0000 Subject: Connectionists: Postdoc position at UCL using Neuropixels probes Message-ID: A postdoctoral position is available in the Neural Computation lab at UCL (http://www.dendrites.org/). The project will involve recordings using next-generation silicon probes, known as "Neuropixels" (http://www.ucl.ac.uk/neuropixels) to investigate computation in neural circuits during behaviour. A paper describing these revolutionary new probes has just been published today in Nature: http://www.nature.com/nature/journal/v551/n7679/full/nature24636.html Neuropixels recordings will be integrated with other techniques being used in the lab such as two-photon microscopy, two-photon optogenetics, and behavioral paradigms in virtual reality. Opportunities exist for collaborations with colleagues in computational neuroscience, engineering, computer science and other fields. UCL is based in central London, with the highest concentration of neuroscience research in the world. The ideal candidate will have a background in systems, computational or cellular neuroscience. Experience with in vivo electrophysiology and/or two-photon microscopy would be an asset, as would strong programming ability in MATLAB or Python. The post is funded for 2 years in the first instance and is available immediately. You should apply for this post (Ref #: 1683637) through UCL's online recruitment website, www.ucl.ac.uk/hr/jobs. Closing date for applications is 26 November 2017. If you are attending the SFN meeting and would like to meet to discuss the position, please contact Michael Hausser (m.hausser at ucl.ac.uk). For any queries regarding the recruitment process please contact Alison Kelly (alison.kelly at ucl.ac.uk). ---------------------------------------------------------- Michael Hausser Wolfson Institute for Biomedical Research University College London Gower Street London WC1E 6BT UK tel +44-20-7679-6756 email m.hausser at ucl.ac.uk http://www.dendrites.org/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From gercek.berk at gmail.com Thu Nov 9 04:35:46 2017 From: gercek.berk at gmail.com (Berk Gercek) Date: Thu, 09 Nov 2017 09:35:46 +0000 Subject: Connectionists: Postdoc positions available in Alex Pouget's lab Message-ID: The laboratory of Alexandre Pouget, at the university of Geneva, will have one, possibly two, postdoc positions available in March 2018. Candidates with strong physics or math background, and with prior experience in computational neuroscience, are encouraged to apply. The topic of research will depend on the interest and profile of the candidate though the lab currently works on decision making, neural coding, probabilistic learning and probabilistic inference in neural circuits. One of these positions will be affiliated with the International Brain laboratory (see https://www.internationalbrainlab.com/). Candidates should send their CV to Alexandre Pouget at alexandre.pouget at unige.ch. -- ---------------------------------------- Berk Gercek Doctoral student, Pouget lab Universit? de Gen?ve 1 rue Michel-servet 1205, Geneva, Switzerland -------------- next part -------------- An HTML attachment was scrubbed... URL: From eilif.mueller at epfl.ch Thu Nov 9 06:07:21 2017 From: eilif.mueller at epfl.ch (Eilif Muller) Date: Thu, 9 Nov 2017 12:07:21 +0100 Subject: Connectionists: EPFL Simulation Neuroscience I - Enrol now on edX.org! Message-ID: <20171109120721.397c6da7@kimchi> Dear Colleagues, I would like to bring to your attention a recently launched Massive Open Online Course (MOOC) on Simulation Neuroscience we are now offering on edX.org, leveraging the HBP Brain Simulation Platform. It is the first of 3 planned MOOCs through which we will teach students to construct and simulate data-driven microcircuits, like the Blue Brain cortical model. More details are below. Many thanks for forwarding to students who may be potentially interested. Best regards, Eilif ===== ANNOUNCEMENT ===== The Center for Digital Education of the ?cole polytechnique f?d?rale de Lausanne (EPFL), Switzerland in cooperation with the Blue Brian Project is welcoming students to participate in a Massive Open Online Course (MOOC) entitled: Simulation Neuroscience I - Reconstruction of a single neuron Faculty: Prof. Henry Markram, Prof. Idan Segev, Prof. Sean Hill, Prof. Felix Schuermann, Samuel Kerrian, Lida Kanari, Werner Van Geit, Dr. Srikanth Ramaswamy, Dr. Eilif Muller Abstract: Simulation Neuroscience is an emerging approach to integrate the knowledge dispersed throughout the field of neuroscience. The aim is to build a unified empirical picture of the brain, to study the biological mechanisms of brain function, behaviour and disease. This is achieved by integrating diverse data sources across the various scales of experimental neuroscience, from molecular to clinical, into computer simulations. In a series of three courses, you will learn to use the state-of-the-art modelling tools of the Human Brain Project Brain Simulation Platform to simulate neurons, build neural networks, and perform your own simulation experiments. This is the first course of the series that will teach you how to digitally reconstruct a single neuron. We invite you to join us and share in our passion to reconstruct, simulate and understand the brain! The course is targeted at senior bachelor, master or PhD students in science or engineering fields looking for an introduction to Simulation Neuroscience. It is a 6 week course, with an estimated course load of 5-7 hours per week. The course is open as of November 2nd, and is self-paced and can be started at any time. For more information: https://www.edx.org/course/simulation-neuroscience-epflx-simneurox ------------- Dr. Eilif Muller Section Manager - Simulation Neuroscience - Cells & Circuits Task Leader - Community Engagement - HBP Brain Simulation SP EPFL - Blue Brain Project Biotech Campus Chemin des Mines 9 1202 Geneva Switzerland Tel: +41 21 693 0698 Fax: +41 21 693 5350 www: http://bluebrain.epfl.ch/page-77926-en.html www: http://neuralensemble.org/people/eilifmuller From kyunghyun.cho at nyu.edu Thu Nov 9 14:16:57 2017 From: kyunghyun.cho at nyu.edu (Kyunghyun Cho) Date: Thu, 9 Nov 2017 19:16:57 +0000 Subject: Connectionists: Director for the Center for Data Science at NYU Message-ID: Director, Center for Data Science New York University (NYU) seeks a director for its Center for Data Science (CDS). Candidates with imagination, energy, and experience are encouraged to apply, and could come from a wide range of professional backgrounds that involve data science. Among the qualities that the director should possess are: - An exceptional research record in data science or related fields. - Scientific leadership and vision. - Experience and capability to manage CDS, including developing new projects and programs, mentoring junior researchers, and administration of the center. - Ability to connect to a wide range of constituents in academia, industry, foundations, and government. The Center for Data Science is located at NYU?s Washington Square campus in the heart of Greenwich Village and shares faculty with the Langone School of Medicine, the Tandon School of Engineering, the Stern School of Business, and the Faculty of Arts & Sciences. It borders many prominent high-tech companies?AIG, Facebook, Google, Microsoft among others?and is part of the neighborhood?s vibrant start-up culture. CDS has a strong interdisciplinary faculty and has established thriving Masters and PhD programs in data science. The director will be responsible for recruiting and maintaining an exceptional faculty and administrative team, attracting high quality students, and building and sustaining partnerships with other units of NYU and in the local entrepreneurial ecosystem. The ideal director will enhance NYU?s prominence as a leader in data science research and education across a range of rapidly evolving fields. To assist in this search, NYU has retained Park Square Executive Search. To nominate a candidate or to express interest in the opportunity in confidence, please email Jonathan Fortescue or Kyle Meingast at nyudatascience at parksquare.com or call 617-401-2991. Applications will receive fullest consideration if received by 19 January 2018. The search will remain open until the position is filled. -------------- next part -------------- An HTML attachment was scrubbed... URL: From barros at informatik.uni-hamburg.de Thu Nov 9 10:26:34 2017 From: barros at informatik.uni-hamburg.de (Pablo Barros) Date: Thu, 9 Nov 2017 16:26:34 +0100 Subject: Connectionists: CFP: Special Issue on Crossmodal Learning Message-ID: CALL FOR PAPERS Special Issue on Computational Models for Crossmodal Learning of the Cognitive Systems Research Journal. https://www.journals.elsevier.com/cognitive-systems-research/ ?I. Aim and Scope The ability of processing crossmodal information is a fundamental feature of the brain that provides a robust perceptual experience for an efficient interaction with the environment. Consequently, the integration of multisensory information plays a crucial role in autonomous systems to create robust and meaningful representations of objects and events. For dealing with real-world information, an autonomous, intelligent system must be capable of processing, integrating, and segregating different modalities for the purpose of coherent perception, decision-making, and cognitive learning. Recent neurophysiological findings in crossmodal learning have inspired novel computational models with the aim to trigger biologically inspired behavioral responses. A rich set of neural mechanisms support the integration and segregation of multimodal stimuli, providing the means to efficiently solve conflicts across modalities. This special issue aims to invite contributors from psychology, computational neuroscience, artificial intelligence, and cognitive robotics to discuss current research on crossmodal learning mechanisms both from the theoretical and modelling perspective. II. Potential Topics Topics include, but are not limited to: - New theories and findings on crossmodal processing - New neuroscientific results on crossmodal learning - Machine learning and neural networks for learning multisensory representations - Computational models of crossmodal attention and perception - Brain-inspired approaches for multisensory integration - Multisensory robot perception III. Submission Authors must use the Evise system to submit their contibutions, more informations can be found here: https://www.journals.elsevier.com/cognitive-systems-research/ *All manuscripts must be submitted to the Special Issue "VSI: Crossmodal Learning"* - Paper submission deadline: 09.02.2018 IV. Guest Editors Pablo Barros, University of Hamburg, Germany German I. Parisi, University of Hamburg, Germany Doreen Jirak, Hamburg University, Germany Bruno Fernandes, Universidade de Pernambuco, Brazil -- Dr.rer.nat. Pablo Barros Research Associate Knowledge Technology Department of Informatics University of Hamburg Vogt-Koelln-Str. 30 22527 Hamburg, Germany Phone: +49 40 42883 2535 Fax: +49 40 42883 2515 barros at informatik.uni-hamburg.de https://www.inf.uni-hamburg.de/en/inst/ab/wtm/people/barros.html www.knowledge-technology.info From frank.ritter at psu.edu Thu Nov 9 19:08:00 2017 From: frank.ritter at psu.edu (Frank Ritter) Date: Thu, 9 Nov 2017 19:08:00 -0500 Subject: Connectionists: CogModel notes: ICCM17-18/confs/resources/Jobs Message-ID: [please forward to your lists please] Hope this finds you well. The ICCM 2018 announcements drive this email. We had an interesting ICCM+MathPsych this year. Proceedings are available. Next meeting will be Madison, WI concurrent with ACT-R and with CogSci. This bulletin was delayed by high work load, and then illness brought about by high work load! Josh Irwin helped prepare this. I've moved it to a mailing list tool at PSU because the previous tool could not email anymore. I believe this change will be relatively invisible. [Hypertext version available at http://acs.ist.psu.edu/iccm2018/iccm-mailing-nov2017.html ] cheers, Frank **************** Table of Contents **************** 1. MathPsych/ICCM 18 will be in Madison, WI http://mathpsych.org/conferences/2018/ 2. ICCM 17 Proceedings has an ISBN http://iccm-conference.org/2017/ http://iccm-conference.org/2017/ICCMprogram_files/proceedingscombined.pdf ** Resources ** 3. OUP CogEng Handbook is online https://courses.engr.illinois.edu/cs598ack/ 4. Books online in Sage, OUP, & Springer, my comments 5. Understanding higher cognition in terms of brain anatomy, physiology & chemistry http://understandinghighercognition.com/ [online book] 6. Frontiers in Psychology journal, sample ToC 7. Book and site about ranking https://aboutranking.com/ 8. SBP-BRiMS 2017 http://sbp-brims.org http://sbp-brims.org/2017/proceedings/ 9. The proceedings for the 37th Soar Workshop are now available http://soar.eecs.umich.edu/workshop/37/ 10. Proceedings From The 13th International Conference of Naturalistic Decision Making https://www.eventsforce.net/uob/media/uploaded/EVUOB/event_2/GoreWard_NDM13Proceedings_2017.pdf 11. Fifth Annual Conference on Advances in Cognitive Systems http://www.cogsys.org/conference/2017 Proceedings: http://www.cogsys.org/conference 12. ACM TOCHI Call for Papers: Special Issue on Human-Building Interaction [Submission Date 8Dec17] 13. A New Thematic Series on ATTENTION IN NATURAL & MEDIATED REALITIES in Cognitive Research: Principles & Implications (CRPI) http://cognitiveresearchjournal.springeropen.com/submission-guidelines 14. Creativity & Intelligence in Brains & Machines Conference http://www.interdisciplinary-college.de/ 15. Scholarship on Model-based Cognitive Neuroscience 16. 4th Annual Summer School on Large-Scale Brain Modeling http://www.nengo.ca/summerschool 17. Soar Has an Updated Wikipedia Article https://en.wikipedia.org/wiki/Soar_(cognitive_architecture) 18. Table of Contents Alert For "Computational & Mathematical Organization Theory" [Date Jun17] http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I0 19. Net neutrality is good for people & business https://www.wired.com/2017/01/dont-gut-net-neutrality-good-people-business/ 20. This is a game aimed at helping people get used to terminal commands http://www.mprat.org/Terminus/ 21. Little AI, free game on iTunes http://little-ai.com/ ** Jobs ** 22. HCI jobs at IST at PSU https://ist.psu.edu/college/faculty_search 23. Post Doc Position Developing an Adaptative Synthetic Teammate Derrik.E.Asher.civ at mail.mil 24. Postdoctoral Fellow in Computational Cognitive Science Central European U, Budapest, Hungary https://cognitivescience.ceu.edu/ 25. Post-doctoral fellow position Dynamic Decision Making Laboratory Department of Social & Decision Sciences Carnegie Mellon U [Prefered Starting Data: 1Oct17] http://www.cmu.edu/ddmlab/ 26. Postdoctoral Fellow in Computational Models of Reasoning [Application deadline 30Jul17] 27. PHD Studies In the Area Of Computational HCI https://www.hict.fi/autumn_2017 [Application deadline 30Jul17] 28. Contract Position Through Leidos http://jobs.leidos.com/ShowJob/Id/989233/Software-Engineer/ 29. Editor Search, Computational Brain & Behavior societyformathpsych at gmail.com **************************************************************** 1. MathPsych/ICCM 18 will be in Madison, WI http://mathpsych.org/conferences/2018/ Call for papers MathPsych/ICCM 18 The 51st Annual Meeting of the Society for Mathematical Psychology, and the 16th Annual Meeting of the International Conference on Cognitive Modelling will meet jointly at the U of Wisconsin in Madison from 21-24 Jul. The organizers from the Society for Mathematical Psychology are Joe Austerweil (U of Wisconsin) and Joe Houpt (Wright State U), and the ICCM chairs are Ion Juvina (Wright State U), Joe Houpt (Wright State U), Christopher Myers (US Air Force Research Laboratory) and Qiong Zhang (CMU). The goal of the conference is to bring researchers together who are interested in using computational and mathematical modeling to better understand human cognition. It is a forum for presenting, discussing, and evaluating the complete spectrum of cognitive modeling approaches, including mathematical models, connectionism, symbolic modeling, dynamical systems, Bayesian modeling, and cognitive architectures. We welcome basic and applied research across a wide variety of domains, ranging from low-level perception and attention to higher-level problem-solving and learning. We also welcome contributions that use computational models to better understand neuroimaging data. The Annual Summer Interdisciplinary Conference will be held before MathPsych/ICCM in Italy on June 17-22. The Annual Meeting of the Cognitive Science Society will be held just following MathPsych - ICCM in Madison on July 25-28. **************************************************************** 2. ICCM 17 Proceedings has an ISBN http://iccm-conference.org/2017/ http://iccm-conference.org/2017/ICCMprogram_files/proceedingscombined.pdf ICCM 17 has an ISBN now, and the revised proceedings are available at http://iccm-conference.org/2017/ http://iccm-conference.org/2017/ICCMprogram_files/proceedingscombined.pdf **************************************************************** 3. OUP CogEng Handbook is online https://courses.engr.illinois.edu/cs598ack/ The OUP Cognitive Engineering Handbook is online, if you have any interest you of course have the option of structuring a course around it. I [Kirlik] found it to be hugely convenient for course design, prep, and delivery, and it makes it convenient (and free) for the students as well. And, in my view at least, class is going very well this semester under this arrangement: https://courses.engr.illinois.edu/cs598ack/ Last time I called it "Cognitive Engineering" but the current title was chosen to be NSF friendly due to the what the students are learning in other grad courses. **************************************************************** 4. Books online in Sage, OUP, & Springer, my comments I'd like to comment on a trend that I've seen. Its both self-serving and I think illuminating. My books with Sage, OUP, & Springer are available, all available, through these companies online libraries. At my U, and at other universities, these books are typically available to all as PDFs (e.g., http://frankritter.com/fducs/fducs-libraries.txt). This has changed the way I think about these books. In most cases, I can say, the book is in your library (which is not news), and your students can have copies for free (which is news). Along with Open Educational Resources (OER), of which there are now deliberate web sites, repositories, and consortium to build them, this ubiquitousness of information, which others have written about more often and more elequently, strikes me as getting closer to actually being here. There is work to automatically create books and associated quizes from these materials. the results are not astounding, on the first pass, but it is the first pass. I think it will come where we have wizard interface to help build custom books for courses that come with draft exams -- at least and perhaps initially for folks at universities that have bought these online libraries, but later for all. **************************************************************** 5. Understanding higher cognition in terms of brain anatomy, physiology & chemistry http://understandinghighercognition.com/ [online book] This came across my email. It looks like an interesting approach. http://understandinghighercognition.com/ **************************************************************** 6. Frontiers in Psychology journal, sample ToC Frontiers In Psychology Section "Cognitive Science" http://journal.frontiersin.org/article/10.3389/fpsyg.2016.00800 Cognitive Appraisals Affect Both Embodiment of Thermal Sensation & Its Mapping to Thermal Evaluation Keeling, Roesch, & Clements-Croome http://journal.frontiersin.org/article/10.3389/fpsyg.2016.00962/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Integrated System Design: Promoting the Capacity of Sociotechnical Systems for Adaptation through Extensions of Cognitive Work Analysis Naikar & Ben http://journal.frontiersin.org/article/10.3389/fpsyg.2016.00976/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Semantic Richness Effects in Spoken Word Recognition: A Lexical Decision & Semantic Categorization Megastudy Winston Goh, Melvin Yap, Mabel Lau, Melvin Ng, & Luuan-Chin Tan http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01017/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Paired-Associate & Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems Kaiyun Li, Qiufang Fu, Xunwei Sun, Xiaoyan Zhou, & Xiaolan Fu http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01010/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Is Moving More Memorable than Proving? Effects of Embodiment & Imagined Enactment on Verb Memory David Sidhu & Penny Pexman http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01005/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Development of Embodied Sense of Self Scale (ESSS): Exploring Everyday Experiences Induced by Anomalous Self-Representation Tomohisa Asai, Noriaki Kanayama, Shu Imaizumi, Shinichi Koyama, & Seiji Kaganoi http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01034/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Semantic Neighborhood Effects for Abstract versus Concrete Words Ashley N. Danguecan & Lori Buchanan http://journal.frontiersin.org/article/10.3389/fpsyg.2016.01033/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 The Neurocognitive Performance of Visuospatial Attention in Children with Obesity Chia-Liang Tsai, Fu-Chen Chen, Chien-Yu Pan, & Yu-Ting Tseng http://journal.frontiersin.org/article/10.3389/fpsyg.2016.00991/full?utm_source=newsletter&utm_medium=email&utm_campaign=Psychology-w32-2016 Editorial: The Balanced Triad of Perception, Action, & Cognition Snehlata Jaswal **************************************************************** 7. Book and site about ranking https://aboutranking.com/ Peter Erdos has started a blog on ranking things, like ranking colleges, ranking basketball teams, and there are some initial posts. ?While he does not have the intention to upload longer parts from the book he is writing on ranking the initail posts look interesting. He is looking for feedback. Worth at aleast a short visit. **************************************************************** 8. SBP-BRiMS 2017 http://sbp-brims.org http://sbp-brims.org/2017/proceedings/ SBP-BRiMS 17 17 International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction & Behavior Representation in Modeling & Simulation (SBP-BRiMS) 5-8Jul17, Lehman Auditorium, George Washington U, Washington DC, USA Conference Website: http://sbp-brims.org/ All papers are qualified for the Best Paper Award. Papers with student first authors will be considered for the Best Student Paper Award. Those receiving these awards will be invited to publish an extended version in a special issue of the journal Computational & Mathematical Organization Theory. IMPORTANT DATES: Regular Paper Abstract Submission: 22dec17 Note, all regular papers will be evaluated for: presentation in plenary, presentation in regular session, presentation as poster, or no presentation. All accepted papers will be published in the physical proceedings - the Springer LNCS volume. This volume is considered archival. There are also challenge problems and tutorials. Social computing harnesses the power of computational methods to study social behavior, such as during team collaboration. Cultural behavioral modeling refers to representing behavior and culture in the abstract, and is a convenient and powerful way to conduct virtual experiments and scenario analysis. Both social computing and cultural behavioral modeling are techniques designed to achieve a better understanding of complex behaviors, patterns, and associated outcomes of interest. Moreover, these approaches are inherently interdisciplinary; subsystems and system components exist at multiple levels of analysis (i.e., "cells to societies") and across multiple disciplines, from engineering and the computational sciences to the social and health sciences. The SBP-BRiMS conference invites modeling & simulation papers from academics, research scientists, technical communities and defense researchers across traditional disciplines to share ideas, discuss research results, identify capability gaps, highlight promising technologies, and showcase the state-of-the-art in applications in the areas of cultural behavioral modeling, prediction, and social computing. Please see the SBP-BRiMS17 website for more details. Keynotes and tutorials delivered in the previous SBP and BRiMS meetings are available through the websites http://sbp-brims.org/ and http://cc.ist.psu.edu/BRIMS2015/ . CALL FOR PAPERS: Submissions are solicited on research issues, theories, and applications. Topics of interests include the following: Advances in Sociocultural & Behavioral Processes * Group interaction and collaboration * Group formation and evolution * Group representation and profiling * Collective action and governance * Cultural patterns & representation * Social conventions, social contexts and processes * Influence process and recognition * Public opinion representation, identification and modeling * Information diffusion * Psycho-cultural situation awareness Behavior Modeling * Intelligent agents and avatars/adversarial modeling * Cognitive robotics and human-robot interaction * Models of reasoning and decision making * Model validation & comparison * Socio-cultural M&S: team/group/crowd/behavior * Physical models of human movement * Performance assessment & skill monitoring/tracking * Performance prediction/enhancement/optimization * Intelligent tutoring systems * Knowledge acquisition/engineering * Human behavior issues in model federations Methodological Challenges * Mathematical foundations * Verification and validation * Sensitivity analysis * Matching technique or method to research questions * Metrics and evaluation * Methodological innovation * Model federation and integration * Evolutionary computing * Optimization Information, Systems, & Network Science * Data mining on social media platforms * Diffusion and other dynamic processes over networks * Inference of network topologies and changes over time * Analysis of link formations and link types * Detection of communities and other types of structures in networks * Analysis of high-dimensional networks * Analytics for social and human dynamics Military & Intelligence Applications * Evaluation, modeling and simulation * Group formation and evolution in the political context * Technology and flash crowds * Networks and political influence * Group representation and profiling * Reasoning about terrorist group behaviors and policies towards them Applications for Health and Well-being * Social network analysis to understand health behavior * Modeling of health policy and decision making * Modeling of behavioral aspects of infectious disease spread * Intervention design & modeling for behavioral health Other Applications * Economic applications of behavioral & social prediction * Viral marketing * Reasoning about development aid through social modeling * Reasoning about global educational efforts through cognitive simulation FORMAT & SUBMISSION: The conference solicits three categories of papers: Regular papers (max. 10 pages) All topics and authors (academic, government, industry) welcome Published in a Springer volume and online. Plenary or poster presentation. Short papers and Late-breaking results (max. 6 pages) All topics and authors welcome. Published online. Typically a poster presentation. Demos (2-page abstract, or max. 6 pages) Published online. Typically a poster or demo presentation. Paper Formatting Guideline The papers must be in English & MUST be formatted according to the Springer-Verlag LNCS/LNAI guidelines. Sample LaTeX2e and WORD files are available at http://www.springer.com/computer/lncs?SGWID=0-164-6-793341-0. It is not required to submit a cover page. All regular paper submissions should be submitted as a paper with a maximum of 10 pages using the foregoing format. All submissions for posters, demo-presentations, challenge problem entries and late breaking results should be submitted as a paper with a maximum of 6 pages using the same format as the regular papers. All accepted entries will be posted on the SBP-BRiMS 17 website. A selection of authors will be invited to contribute journal versions of their papers to one of two planned special issues of the Springer journal "Computational & Mathematical Organization Theory" and another high- profile journal. The submission website will be available through http://sbp-brims.org/2018/cfp/ PRE-CONFERENCE TUTORIAL SESSIONS: Several half-day sessions will be offered on the day before the full conference. Sessions will be designed to meet the needs of one of two distinct groups. One group will consist of attendees who have backgrounds in computational science; computer science, engineering, and other mathematically oriented disciplines. Other tutorial sessions will be designed for behavioral and social scientists and others (e.g. those with medical backgrounds or training in public health) who may have limited formal education in the computational sciences. Attendees will gain an understanding of terminology, theories, and general approaches employed by computationally based fields, especially with respect to modeling approaches. At minimum, each proposal must contain the following information: * Title of the tutorial. * Description of the tutorial topic & structure. * Expected audience (including the expected backgrounds of the attendees). * Short bio & contact information of the organizers. More details regarding the pre-conference tutorial sessions, including instructors, course content, and registration information will be posted to the conference website (SBP-BRiMS.org) as soon as this information becomes available. For further information, please contact sbpbrims at andrew.cmu.edu. CHALLENGE: The conference expects to announce a computational challenge as in previous years. Additional details will be posted on the conference website. FUNDING PANEL & CROSS-FERTILIZATION ROUNDTABLES: Previous SBP-BRiMS conferences have included a Cross-fertilization Roundtable session or a Funding Panel. The purpose of the cross- fertilization roundtables is to help participants become better acquainted with people outside of their discipline and with whom they might consider partnering on future SBP-BRiMS-related research collaborations. The Funding Panel provides an opportunity for conference participants to interact with program managers from various federal funding agencies. Participants for the previous funding panels have included representatives from federal agencies, such as the NSF, NIH, DoD, ONR, AFOSR, USDA, etc. BEST PAPER AWARDS: SBP-BRiMS17 will feature a Best Paper Award and a Best Student Paper Award. All papers are qualified for the Best Paper Award. Papers with student first authors will be considered for the Best Student Paper Award. HOTEL & LOGISTICS: Information on hotel and logistics will be provided at the conference website as it becomes available. TRAVEL SCHOLARSHIPS: It is anticipated that a limited number travel scholarships will be available on a competitive basis. Additional information will be provided on the SBP- BRiMS Conference website as it becomes available. **************************************************************** 9. The proceedings for the 37th Soar Workshop are now available http://soar.eecs.umich.edu/workshop/37/ The proceedings for the 37th Soar Workshop, which was held on 5-9Jun at the U of Michigan campus, are now available online. You can find digital copies of all of the presentations that were given on http://soar.eecs.umich.edu/workshop/37/ **************************************************************** 10. Proceedings From The 13th International Conference of Naturalistic Decision Making https://www.eventsforce.net/uob/media/uploaded/EVUOB/event_2/GoreWard_NDM13Proceedings_2017.pdf The 13th International Conference of Naturalistic Decision Making, which was held in Bath, England 20-23Jun17. Has released its proceedings from the 13th bi-annual conference. The conference encapsulates the cognitive challenges associated with making decisions in demanding and uncertain situations. It is co-chaired by Gore & Ward. Keynote speakers include Rhona Flin & Nassim Nicholas Taleb. Gary Klein, Ph.D. MacroCognition LLC 937/238-8281 (cell) gary at macrocognition.com www.macrocognition.com & check our new web site: http://www.shadowboxtraining.com **************************************************************** 11. Fifth Annual Conference on Advances in Cognitive Systems http://www.cogsys.org/conference/2017 Proceedings: http://www.cogsys.org/conference The proceedings for the Fifth Annual Conference on Advances in Cognitive Systems is now available online. It can be found here: http://www.cogsys.org/conference/2017 Paper submissions will be handled via the EasyChair website (http://www.easychair.org), and login instructions will be posted as an update to the link given above within the next two weeks. Any questions you may have should be forwarded to paul.bello at nrl.navy.mil We look forward to seeing you in May! With our warmest regards, Paul Bello, Chair Ken Forbus, Ashok Goel, John Laird, Pat Langley & Sergei Nirenberg, ACS Organizing Committee **************************************************************** 12. ACM TOCHI Call for Papers: Special Issue on Human-Building Interaction [Submission Date 8Dec17] Call For Papers ACM Transactions on Computer-Human Interaction (TOCHI) Special Issue on Human-Building Interaction Guest Editors: Hamed Alavi, U of Fribourg & Swiss Federal Institute of Technology (EPFL) Elizabeth Churchill, Google, Mountain View Mikael Wiberg, Umea U Denis Lalanne, U of Fribourg Peter Dalsgaard, Aarhus U Ava Fatah gen Schieck, UCL, Bartlett School of Architecture Yvonne Rodgers, U College London & TOCHI Editorial Board Information for Contributors Built environments increasingly incorporate interactivity and context-aware automation. Human-Building Interaction (HBI), as an emerging research field, seeks to develop an HCI lens to the vision of our interactive experiences with built environments. A special issue of TOCHI on Human-Building Interaction invites research contributions that examine the engagement of HCI in the evolution of buildings & urban spaces. In particular, we solicit articles that pursue the new coordinates that HCI should take into account when shifting attention and scale from "artefact" to "environment." For example, the investigations on the occupant comfort across multiple dimensions (e.g., thermal, visual, acoustic, respiratory), the discussions of the interplay between user agency and building automation, the reflections on the immersive and durable user experience design, and so forth. We seek contributions that address these and similar topics that embody the complexity of human's individual and collective experiences with and within the built environment. The invited topics include technological innovations, ethnographic studies, as well as conceptual and framing contributions. Between the lofty and mundane discourses of interactive architecture and connected products lies considerable space for grounded research and reflective discussion. This special issue invites attempts to capture, share, and expand what is already known, what is contested, and what are opportunities for a common scientific grounding for prospective dialogues and discourses in the area of Human-Building Interaction. It will serve both as a unifying stage for the existing voices that are centrally and peripherally working on HBI, and a platform for the research area to move forward. The HBI special issue is interested in questions including (but not limited to) the following: How can HBI designers reconcile the complexity of human decisions with the efficiency that the automation systems promise? What services do we expect the building to provide seamlessly, and where do we want to retain the manipulation control, and through what interaction modalities? What are the UX design challenges in creating buildings that can adapt to their occupants' contextualized needs and preferences? Surveillance is increasingly common to provide security. How does the need for surveillance interplay with the privacy concerns which are especially elevated in inhabited environments? What can we learn from the comfort literature in the scholarly domain of architecture, and how can an HCI perspective complement and (possibly) correct the current comfort discourses? In what ways can built environments support and take advantage of social and cultural diversity? Are architecture and interaction design methods and processes compatible? Concretely, how can a team of interaction designers bring their tools to an architectural project? Submission Information All contributions will be rigorously peer reviewed to the usual exacting standards of TOCHI. Further information, including TOCHI submission procedures and advice on formatting and preparing manuscripts, can be found at: https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16171x312a19x011022& Manuscripts must be submitted via the ACM online manuscript system to: https://orange.hosting.lsoft.com/trk/click?ref=znwrbbrs9_6-16171x312a1ax011022& Important Dates Pre-Submission Abstract Due: 8Dec17 (email to HBI-TOCHI at unifr.ch) Full Manuscript Submission deadline: 12Jan18 (submit via http://mc.manuscriptcentral.com/tochi) First-round Author Notifications: 15Apr18 First-round Revisions due: 15Jun18 Second-round (final) Author Notifications: 1Sept18 Final Revisions Due: 10Oct18 Publication Date: February19 Please direct inquiries regarding the special issue to HBI-TOCHI at unifr.ch **************************************************************** 13. A New Thematic Series on ATTENTION IN NATURAL & MEDIATED REALITIES in Cognitive Research: Principles & Implications (CRPI) http://cognitiveresearchjournal.springeropen.com/submission-guidelines Announcing a new special issue or, as we say in the Open Access, On-Line World, A New Thematic Series on Attention In Natural & Mediated Realites in Cognitive Research: Principles & Implications (CRPI) Co-organizers: Jeffrey Zacks, Washington U in Saint Louis, jzacks at wustl.edu Khena Swallow, Cornell, kms424 at cornell.edu Daniel Levin, Vanderbilt, daniel.t.levin at Vanderbilt.edu Modern humans live in natural environments and in worlds shaped and mediated by technology. Both of these worlds are complex, dynamic, and rich; producing streams of data that vastly outstrip the capacities of human cognitive systems. Yet, people usually understand and intelligently act in everyday situations. How do people use attention to manage environmental demands on human cognitive systems? The purpose of this collection of papers is to examine how attention operates in environments that approach the complexity of naturalistic situations. Papers may be empirical studies, theoretical or tutorial reviews, or new theoretical contributions. Studies using behavioral, neurophysiological, and/or eye-tracking methods would all be appropriate. Issues of particular interest include: the role of attention in media consumption & education; change blindness and inattentional blindness in naturalistic settings; motivation, reward, and attention; curiosity; predictive looking in event comprehension. (This list is not exclusive.) Please email one or more of the guest editors with any questions about submissions. CRPI is the open access journal of the Psychonomic Society. Its mission is to publish use-inspired basic research: fundamental cognitive research that grows from hypotheses about real-world problems. As with all Psychonomic Society journals, submissions to CRPI are subject to rigorous peer review. For manuscripts accepted for the special issue, the publication fee may be fully or partially waived depending on the number of manuscripts accepted for the special issue. The authors should indicate when they submit a manuscript if they are requesting a waiver of the publication fee. DUE DATE: manuscripts should be submitted before 31Dec17 You can find manuscript submission details at http://cognitiveresearchjournal.springeropen.com/submission-guidelines **************************************************************** 14. Creativity & Intelligence in Brains & Machines Conference http://www.interdisciplinary-college.de/ This is an unsual event, that appears to repeat. It looks like a transitory, 'invisible college', (Reference: https://en.wikipedia.org/wiki/Invisible_College), that gets created to look at issues of across scientific fields, but is fact probably held together by a core group of some sort. **************************************************************** 15. Scholarship on Model-based Cognitive Neuroscience http://www.rug.nl/education/phd-programmes/phd-scholarship-programme/phd-scholarships?details=00347-02S0005SGP Scholarship on Model-based Cognitive Neuroscience The Institute of Artificial Intelligence of the U of Groningen offers a four-year scholarship for a PhD position on model-based cognitive neuroscience. Model-based cognitive neuroscience is the area of research that bridges the disciplines of computational cognitive modeling & cognitive neuroscience. Cognitive models - be it symbolic process models, mathematical models, or neural network models - are notoriously hard to evaluate based on behavioral measures alone. For that reason, researchers have turned to neuroscience (M/EEG, fMRI) as an additional source of information. At the same time, neuroimaging data is often so complex that it is difficult to fully account for with traditional analysis methods. As a solution, cognitive & mathematical models have been used within the analysis stream to interpret neural measures directly. This dual approach, using neuroscience to inform models and models to inform neuroimaging analyses, is very powerful, and has led to the emerging field of model-based cognitive neuroscience (see a recent special issue of the Journal of Mathematical Psychology for an introduction: Palmeri, Love, & Turner, 17; Turner, Forstmann, Love, Palmeri, & van Maanen, 17). The PhD position is available in the cognitive modeling group, under supervision of Jelmer Borst. The goal of our group is to better understand cognitive processes in the human mind. To achieve this, we combine computational modeling with fMRI, EEG, & MEG data, and also apply machine learning techniques to analyze neural data. Top candidates will be invited to write & develop their own research project within the general scope of this research line. The selection procedure for the scholarship is as follows: 1. Candidates apply by submitting a cover letter & CV (see below for details). 2. Based on the cover letters, several candidates will be invited to write a short research proposal within the topic of model-based neuroscience. 3. These candidates will be asked to present this proposal as part of the job interview. 4. After the selection, the candidates proposal will be further developed in collaboration with the PhD advisors: Jelmer Borst, Niels Taatgen, & Hedderik van Rijn. Qualifications Successful candidates will have completed a Masters degree (or equivalent) in Cognitive Neuroscience, Artificial Intelligence, or another field of science relevant for the position. The ideal candidate has experience with M/EEG or fMRI and cognitive modeling, and has strong programming skills. Conditions The PhD student will be enrolled in the PhD Scholarship Programme and receive a scholarship of E 2027 per month (gross) from the U of Groningen for a period of four years. Date The preferred start date is 1Nov17, but this can be postponed to 1Feb18. Application Please see the attachment for details on the application procedure. The application deadline is 30Aug. For more information, contact Jelmer Borst (j.p.borst at rug.nl). http://www.rug.nl/education/phd-programmes/phd-scholarship-programme/phd-scholarships?details=00347-02S0005SGP **************************************************************** 16. 4th Annual Summer School on Large-Scale Brain Modeling http://www.nengo.ca/summerschool [this happened, but looks like a standing meeting now] The Centre for Theoretical Neuroscience at the U of Waterloo is inviting applications for our 4th annual summer school on large-scale brain modeling. This two-week school will teach participants how to use the Nengo software package to build state-of-the-art cognitive and neural models to run in simulation and on neuromorphic hardware. Nengo has been used to build what is currently the world's largest functional brain model, Spaun [1], and provides users with a versatile and powerful environment for designing cognitive and neural systems to run in simulated and real environments. For a look at last year's summer school, check out this short video: https://goo.gl/EkhWCJ We welcome applications from all interested graduate students, research associates, postdocs, professors, and industry professionals. No specific training in the use of modeling software is required, but we encourage applications from active researchers with a relevant background in psychology, neuroscience, cognitive science, robotics, neuromorphic engineering, computer science, or a related field. [1] Eliasmith, C., Stewart T. C., Choo X., Bekolay T., DeWolf T., Tang Y., Rasmussen, D. (2012). A large-scale model of the functioning brain. Science. Vol. 338 no. 6111 pp. 1202-1205. DOI: 10.1126/science.1225266. [http://nengo.ca/publications/spaunsciencepaper] ***Application Deadline: 15Feb17*** Format: A combination of tutorials & project-based work. Participants are encouraged to bring their own ideas for projects, which may focus on testing hypotheses, modeling neural or cognitive data, implementing specific behavioural functions with neurons, expanding past models, or providing a proof-of-concept of various neural mechanisms. Hands-on tutorials, work on individual or group projects, and talks from invited faculty members will make up the bulk of day-to-day activities. A project demonstration event will be held on the last day of the school, with prizes for strong projects! Topics Covered: Participants will have the opportunity to learn how to: build perceptual, motor, and sophisticated cognitive models using spiking neurons model anatomical, electrophysiological, cognitive, and behavioural data use a variety of single cell models within a large-scale model integrate machine learning methods into biologically oriented models interface Nengo with various kinds of neuromorphic hardware (e.g. SpiNNaker) interface Nengo with cameras & robotic systems implement modern nonlinear control methods in neural models & much more. Date & Location: 4-16 Jun17 at the U of Waterloo, Ontario, Canada. Applications: Please visit http://www.nengo.ca/summerschool, where you can find more information regarding costs, travel, lodging, along with an application form listing required materials. If you have any questions about the school or the application process, please contact Peter Blouw (pblouw at uwaterloo.ca). We look forward to hearing from you! **************************************************************** 17. Soar Has an Updated Wikipedia Article https://en.wikipedia.org/wiki/Soar_(cognitive_architecture) Soarers, [from soar mailing list] We just updated (and significantly expanded) the entry for Soar on Wikipedia. Check it out and feel free to add material. **************************************************************** 18. Table of Contents Alert For "Computational & Mathematical Organization Theory" [Date Jun17] http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I0 We are pleased to deliver your requested table of contents alert for "Computational & Mathematical Organization Theory". Volume 23 Number 2 is now available on SpringerLink http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I0 ================================================================= Change the World: Read 180 articles nominated by our Editors-in-Chief We asked our Editors-in-Chief to nominate just one journal article published in 2016 that could help humanity and protect and preserve our planet. Read 180 groundbreaking articles that have the potential to change the world! All selected articles are freely accessible! http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I1 ================================================================= IN THIS ISSUE: How resource information backgrounds trigger post-merger integration & technology innovation? A dynamic analysis of resource similarity & complementarity Feiqiong Chen, Qiaoshuang Meng & Fei Li Abstract: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I2 Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I3 >>>Generic substitution policy, an incentive approach<<< Aida Isabel Tavares Abstract: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I4 Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I5 >>>Self-organization & social science<<< David Anzola, Peter Barbrook-Johnson & Juan Cano Abstract: ---http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I6 Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I7 >>>Integrating accounting & multiplicative calculus: an effective estimation of learning curve<<< Hasan zyap lhan Dalc & Ali zyap Abstract: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I8 Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9I9 >>>The interpersonal diffusion mechanism of unethical behavior in groups: a social network perspective<<< Duanxu Wang, Xin Pi & Yuhao Pan Abstract: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ia Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ib >>>Corruption & its detection: a graph-theoretic approach<<< Thebeth Rufaro Mukwembi & Simon Mukwembi Abstract & PDF http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ic http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Id Reporting a network's most-central actor with a confidence level Frantz & Carley Abstract: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ie Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9If >>>Book review: The Journal of Organizational Design<<< Terrill Frantz Abstract: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ig Full text PDF: http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ih ________________________________________________________________________ Do you want to publish your article in this journal? Please visit the homepage of Computational & Mathematical Organization Theory http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ii for full details on: - aims & scope - editorial policy - article submission ________________________________________________________________________ Read open access articles Anyone can access open access articles for free. Go to http://alerts.springer.com/re?l=D0In66plwI6hi0lc9Ij to view all open access articles published in this journal. **************************************************************** 19. Net neutrality is good for people & business https://www.wired.com/2017/01/dont-gut-net-neutrality-good-people-business/ Net neutrality is good for people & business. Preserving net neutrality will help "make America great again." My article featured in Wired. Wired, https://www.wired.com/2017/01/dont-gut-net-neutrality-good-people-business/ Don't Gut Net Neutrality. It's Good for People & Business, 5Jan17 Best, Nick http://www.stern.nyu.edu/networks/ **************************************************************** 20. This is a game aimed at helping people get used to terminal commands http://www.mprat.org/Terminus/ http://www.mprat.org/Terminus/ - This is a game aimed at helping people get used to terminal commands (i.e., those you'd see in Unix-based terminals). I got the link to this from another professor here. I'm going to try to use it for our 1st lab for our 2nd intro course. **************************************************************** 21. Little AI, free game on iTunes http://little-ai.com/ Little AI is our free game for iPhone or iPad to illustrate developmental artificial intelligence and constructivist learning. It can be used for teaching. It was just released on the App store: http://little-ai.com/ https://itunes.apple.com/us/app/id1114007742 contact: Olivier Georgeon olivier.georgeon at gmail.com **************************************************************** 22. HCI jobs at IST at PSU https://ist.psu.edu/college/faculty_search [IST has jobs going in HCI, data science, and related areas. If you apply, let me or Reitter know so I can keep my eyes out for your application.] The College of Information, Science, and Technology at Penn State has open tenure-track positions for Human Centered Design, Data Sciences, and Security & Privacy. Most positions will begin reviewing applications in mid-Oct, but will remain open until the position is filled. Teaching Faculty Positions in Application Design and Development, Cybersecurity Analytics and Operations [Application Review 1Sep17] https://ist.psu.edu/node/3080 Open Rank, Tenure-Track, Faculty Positions in Data Sciences- Ethics [Application Review 15Oct17, Open until filled] https://ist.psu.edu/node/3094 Open Rank, Tenure-Track, Faculty Positions in Human Centered Design [Application Review 1Oct17, Open until filled] https://ist.psu.edu/node/3219 Open Rank, Tenure-Track, Faculty Positions in Security and Privacy [Application Review 1Oct17, Open until filled] https://ist.psu.edu/node/3220 Open Rank, Tenure-Track, Faculty Positions in Data Sciences [Application Review 1Dec17, Open until filled] https://ist.psu.edu/node/3223 **************************************************************** 23. Post Doc Position Developing an Adaptative Synthetic Teammate Derrik.E.Asher.civ at mail.mil The United States Army Research Laboratory (ARL) is seeking applications for one postdoctoral position to support research in the development of an adaptive synthetic teammate to the Soldier. The post-doc position requires conducting applied and basic research to inform theoretical and empirical principles for developing algorithms designed to interact with humans in simulated or physical environments. Potential topics of research include: (1) human-computer interaction, human-robot interaction, adaptive computation, or cognitive computing, (2) modeling cognitive processes, developing computational models of human behavior, or (3) mathematical models of physical systems. U.S. citizenship is required. Please see the attached for additional details. To apply for this position, please send a current copy of your CV to: Derrik Asher, Ph.D. Multilingual Computing & Analysis Branch, Computational & Information Sciences Directorate, U. S. Army Research Laboratory Derrik.E.Asher.civ at mail.mil **************************************************************** 24. Postdoctoral Fellow in Computational Cognitive Science Central European U, Budapest, Hungary https://cognitivescience.ceu.edu/ We are seeking a highly creative and motivated postdoctoral fellow to work in the group of Mate Lengyel at the Department of Cognitive Science, Central European U, Budapest, Hungary (https://cognitivescience.ceu.edu/). The group is also twinned by the Lengyel group at the Computational & Biological Learning Lab, Department of Engineering, U of Cambridge (http://learning.eng.cam.ac.uk/Public/Lengyel/) where Dr Lengyel holds a permanent position. The group studies learning & memory from computational, algorithmic/representational & neurobiological viewpoints. Computationally & algorithmically, we use ideas from Bayesian approaches to statistical inference and reinforcement learning to characterise the goals and mechanisms of learning in terms of normative principles and behavioral results. Specifically, the project will characterise how human?*?s structured and high dimensional mental representations change in time due to forgetting, learning, interference, and other processes. For this, state-of-the-art machine learning techniques will be employed to analyse a diverse set of behavioural data sets collected by our experimental collaborators: Gergely Csibra (infant studies) and Jozsef Fiser (visual perception & learning) in Budapest, and Daniel Wolpert (sensorimotor control) in Cambridge. The project is funded by an ERC grant, providing internationally competitive salaries. The successful candidate will have - a strong quantitative background - demonstrable interest in the analysis of behavioural data - obtained (or be close to the completion of) a PhD or equivalent in computational neuroscience, physics, mathematics, computer science, machine learning or a related field Preference will be given to candidates with - previous experience in machine learning, computational and / or behavioural neuroscience - sufficient programming skills to run numerical simulations (eg. in C, Python, or MatLab) - expertise with advanced data analysis & Bayesian techniques Research environment: The Central European U is the highest-ranked U in Hungary. It is a privately funded and endowed, fully English-speaking, postgraduate-only U, accredited in both the USA & Hungary. The Department of Cognitive Science is one of the most highly regarded centres for cognitive science in Europe, with world-leading groups in infant cognition, visual cognition, and social cognitive science. It provides a vibrant research environment, by running two journal club events per week on selected topics in cognitive science, a monthly research club, a weekly series of guest seminars by invited speakers from around the globe, a visitors programme with about two-three leading researchers in the field spending several months at the Department every year, and various small-to-medium sized international workshops, conferences, and summer schools organised locally by members of the Department. More broadly, Budapest is an exciting city, with a rich history & busy cultural life, great cuisine, and a very affordable cost of living index. For informal queries, please contact M. Lengyel m.lengyel at eng.cam.ac.uk. Applications will be accepted until the post is filled. Mate Lengyel -- Department of Cognitive Science Central European U Oktober 6 street 7, Budapest H-1051, Hungary tel: +36 1 887 5142 fax: +36 1 887 5010 Computational & Biological Learning Lab Cambridge U Engineering Department Trumpington Street, Cambridge CB2 1PZ, UK tel: +44 (0)1223 748 532, fax: +44 (0)1223 332 662 web: www.eng.cam.ac.uk/~m.lengyel **************************************************************** 25. Post-doctoral fellow position Dynamic Decision Making Laboratory Department of Social & Decision Sciences Carnegie Mellon U http://www.cmu.edu/ddmlab/ [may be late, but she has a steady stream of positions] Post-doctoral fellow position Dynamic Decision Making Laboratory Department of Social & Decision Sciences Carnegie Mellon U (CMU). The Dynamic Decision Making Laboratory (DDMLab: http://www.cmu.edu/ddmlab/) at Carnegie Mellon U is seeking applications for a post-doctoral fellow position on decisions from experience and network science. Starting date is flexible, but it is preferred on 1Oct17. Description: Our general goal in this project is to build upon the insights of Decisions from Experience (DfE) research and expand these insights to Network Science. In particular, we will focus on investigating the effects of information and incentive structures in network-based choices from experience. We will conduct experimental studies involving more than 2 group members, and we will build new computational models to represent the global effects of team behavior built from individual behavior. Specifically, we will work on: (1) systematic expansions of mechanisms of instance-based learning theory (IBLT) (Gonzalez et al., 2003) through the inclusion of methods known in social dilemmas and network science research; (2) the empirical investigation of the interaction between information, incentives, and network structure on efficient networks and social welfare; and (3) the computational implementation of cognitive models to test new theoretical expansions against experimental data. A fellow will collaborate directly with Prof. Gonzalez and with researchers at other institutions. RRequired qualifications: -- A Ph.D. (completed by start of employment) in psychology, economics, decision sciences, computer science, human factors engineering, or any other relevant scientific discipline -- Training in behavioral science research methods & statistical analyses. -- Experience with statistical software (preferably R, others acceptable) -- Experience with computational/cognitive modeling (e.g., reinforcement learning, ACT-R models, IBL models) -- Demonstrable writing abilities and good communication skills. Desired qualifications: -- Experience with programming (preferably Python, others acceptable) -- Experience with web programming and design -- Experience in interdisciplinary research, working in collaborative teams, and managing research assistants Duration: This is a full time research position with full benefits, for one year with the expectation of renewal for additional years conditional on performance and availability of funds. To apply: please send a letter of interest, curriculum vitae, relevant journal articles, and three letters of reference before 15Sept17. Please send electronic documents (Word, Pdf) to: coty at cmu.edu The DDMLab is part of the Department of Social & Decision Sciences at CMU, a research paradise. CMU is located Pittsburgh, Pennsylvania, is one of America'smost livable cities. The city has a strong U presence with over a dozen colleges and campuses and a great cultural scene. Carnegie Mellon is an equal opportunity/affirmative action employer. For more information on our Equal Employment/Affirmative Action Policy and our Statement of Assurance, go to: http://www.cmu.edu/policies/documents/SoA.html **************************************************************** 26. Postdoctoral Fellow in Computational Models of Reasoning [this has passed, but this group routinely hires folks as post-docs, so if you match, you should keep them on your radar when you need such a position.] ----------------------------------------------------------- Postdoctoral Fellow in Computational Models of Reasoning Intelligent Systems Section Navy Center for Applied Research in Artificial Intelligence ----------------------------------------------------------- The Artificial Intelligence Center at the Naval Research Laboratory (NRL) is seeking applicants for multiple postdoctoral positions to collaborate on ongoing development towards a unified computational framework of explanatory and deductive reasoning. The postdoc will develop his or her own research program in addition to working with Dr. Sunny Khemlani & Dr. Greg Trafton at NRL's headquarters in Washington, DC. The position will involve building and applying computational models to simulate human reasoning data. Recent work in the lab has focused on how people engage in explanatory reasoning, how they reason about causality, and how they reason about time and temporal relations. The ideal candidate has (or will have) a Ph.D. in computer science, cognitive science, cognitive psychology, or a related discipline, as well as a strong foundation in computer programming and an interest in building intelligent agents that reason the way humans do. Postdocs will be hired through the NRC Research Associateship Program, and the fellowship lasts up to 3 years. Funding includes a yearly stipend ($77,000) as well as travel, relocation, and health benefits. Only US citizenship or green card holders are eligible for the program. The Intelligent Systems Section at the Navy Center for Applied Research in Artificial Intelligence is devoted to basic and applied research in human cognition. The lab is interdisciplinary and focuses on cognitive science, reasoning, cognitive robotics, human-robot interaction, embodied cognition, spatial cognition, object recognition, memory, and categorization. Applicants should send a letter of interest and a curriculum vitae to Dr. Sunny Khemlani (sunny.khemlani at nrl.navy.mil). Review of applications will begin 15Aug17. * PhD position in the area of computational HCI (4 years, fully funded) (Application deadline 30Jul17) * **************************************************************** 27. PHD Studies In the Area of Computational HCI https://www.hict.fi/autumn_2017 [also late, but looks like a group that will have positions next year.] PHD Studies In the Area of Computational HCI As part of a broader call for PhD students in the area of CS (HICT), the User Interfaces group at Aalto U is looking for a PhD student to join their team. The research topics include fundamental aspects of computational interaction, and in particular interface optimization, interactive machine learning, cognitive and neuroscientific modeling, interactive support for designers, as well as applications. The successful candidate will join an ambitious research group that is at the forefront of this exciting research area. The group offers a collegiate and stimulating environment as well as access to state-of-the-art equipment. The group invites applications from outstanding individuals with motivation and demonstrated technical competence in Computer Science, Data Sciences, Machine Learning, Signal Processing, Statistics, Information Visualization, Computer Graphics, Operations Research, Neurosciences, or Cognitive Science. An interdisciplinary perspective and experience is valued. More about the group: http://userinterfaces.aalto.fi More about the PI: http://users.comnet.aalto.fi/oulasvir/ BACKGROUND: THE HICT EDUCATION NETWORK The Helsinki Doctoral Education Network in Information & Communications Technology (HICT) is a joint initiative by Aalto U and the U of Helsinki, the two leading universities within this area in Finland. The network involves at present over 60 professors and over 200 doctoral students, and the participating units graduate altogether more than 40 new doctors each year. The activities of HICT are structured along five research area specific tracks: Algorithms & machine learning, Life science informatics Networks, networked systems & services, Software and service engineering and systems, User centered & creative technologies For more information on the general call, go to "https://www.hict.fi/autumn_2017". APPLICATION The online application form closes 30Jul17, at midnight Finnish time. For more information & application instructions, see "http://www.hict.fi". **************************************************************** 28. Contract Position Through Leidos http://jobs.leidos.com/ShowJob/Id/989233/Software-Engineer/ [probably quite old, but this group routinely takes on post-docs. if you fit, look them up at Wright Pat AFB, you should keep them on your radar, pun intended.] http://jobs.leidos.com/ShowJob/Id/989233/Software-Engineer/ The position at the link below is a contract position through Leidos, working on an exciting new line of applied research & development with our Cognitive Models & Agents branch at Wright-Patterson AFB. If you have the required knowledge, skills, experience, and interest, please apply at their website. If you know someone else who does, please forward for their awareness. Best regards & happy holidays. - Kevin Kevin Gluck, PhD Principal Cognitive Scientist **************************************************************** 29. Editor Search, Computational Brain & Behavior societyformathpsych at gmail.com [date may have passed, but sometimes are extendable, and notes new editor coming and new journal] The Society for Mathematical Psychology seeks a dynamic, well-organized scientist with high editorial standards and strong leadership skills to serve as the first editor of the new journal Computational Brain & Behavior. SMP aims for CB&B to have a broad scope, accepting work from psychology, neuroscience, economics, and statistics, linked by a common theme of quantitative modeling and methods. CB&B is owned by SMP and will be published by Springer with 4 issues a year. Applicants should be respected leaders in the community, independent-minded, and even-handed. As Editor you should be (1) committed to establishing CB&B as a leading journal in the area of quantitative psychology and neuroscience, (2) proactive in attracting innovative contributions in both traditional disciplines and emerging fields, and (3) able to implement a rigorous and prompt review process. As Editor you will 1. Set the aims and scope for CB&B in consultation with the SMP executive board 2. Select an editorial team ? Have full authority to accept or reject submissions 3. Handle the review process 4. Seek out stimulating papers and special issue topics for inclusion in the journal The new Editor will be appointed for a 5-year term, beginning 1Nov17. Applications should include a curriculum vita, a vision statement for CB&B, and a cover letter. Applications should be submitted to SMP Secretary/Treasurer Leslie Blaha via EMAIL to the email address: societyformathpsych at gmail.com with subject header: CB&B Editor Application: . A search committee along with the executive board of SMP will evaluate candidates. The executive board will make the final selection and appointment. *The deadline for applications is 30Sep17* For more information about CB&B and the application process, please contact SMP President Jennifer Trueblood (jennifer.s.trueblood at vanderbilt.edu) or anyone on the SMP Executive Board (Scott Brown, Clintin Davis-Stober, Chris Donkin, Pernille Hemmer). -30- From malin.sandstrom at incf.org Fri Nov 10 04:53:49 2017 From: malin.sandstrom at incf.org (=?UTF-8?Q?Malin_Sandstr=C3=B6m?=) Date: Fri, 10 Nov 2017 10:53:49 +0100 Subject: Connectionists: Tool & resource demos in INCF's booth #3416 at SfN Message-ID: Hello all, [and apologies for cross-posting] if you are attending SfN in Washington you are most welcome to visit INCF's booth 3416, located near the major funder booths. We have demos all exhibit days of tools and resources from our community -- databases, atlases, infrastructure for neuroimaging -- and our projects KnowledgeSpace and TrainingSpace. Full schedule below. We also have some nice giveaways in exchange for completing our brief community survey, and a comfortable sofa to rest in between posters. More details here: https://www.incf.org/node/235 Welcome! Malin Sandstr?m INCF BOOTH SCHEDULE: Sunday Nov 12 -------------------- INCF Japan Node: 9:30-10:45 INCF Japan Node Platforms I: Brain Transcriptome Database (BrainTx) 9:30-10:45 INCF Japan Node Platforms I: Mouse Phenotype Database 10:45-12:00 INCF Japan Node Platforms II: Cerebellar Platform provides SNS and cloud system 10:45-12:00 Collaboration in INCF Japan Node: Demonstration of the Brain/MINDS Marmoset Brain Atlas 12:00-13:00 INCF Japan Node Platforms II: ViBrism Database: New platform for transcriptome mapping and analysis 12:00-13:00 Collaboration in INCF Japan Node: ModelDB: Demonstration and online simulation at Simulation Platform INCF Norway Node 13:30-15:15 Workflow for automated quantification and spatial analysis of labelling in microscopic rodent brain sections 15:15-17:00 Interactive tools for registration of 2-D and 3-D images into rodent reference atlases 13:30-17:00 F1000 channel Q&A with Jens Foell Monday Nov 13 --------------------- All day: demos of TrainingSpace and KnowledgeSpace 11:00-14:00 F1000 channel Q&A with Jens Foell Tuesday Nov 14 ---------------------- INCF Australia Node 9:30-11:15 NeuroImaging Analysis (NiAnalysis): software for archive-centred analysis of neuroimaging data INCF Canada Node 11:15-11:40 Brain-CODE 11:40-12:05 LORIS : open source databasing and project management 12:05-12:30 CBRAIN: computing platform for neuroscience 12:30-13:00 Online training for reproducible neuroimaging 11:00-14:00 F1000 channel Q&A with Jens Foell 16:00-17:00 Neurodata Without Borders 2.0 - Presentation and Q&A Wednesday Nov 15 --------------------------- Morning: demos of TrainingSpace and KnowledgeSpace -- Malin Sandstr?m, PhD Community Engagement Officer malin.sandstrom at incf.org International Neuroinformatics Coordinating Facility Karolinska Institutet Nobels v?g 15 A SE-171 77 Stockholm Sweden http://www.incf.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From i.jonathan.grainger at gmail.com Fri Nov 10 10:39:43 2017 From: i.jonathan.grainger at gmail.com (Jonathan Grainger) Date: Fri, 10 Nov 2017 16:39:43 +0100 Subject: Connectionists: post-doc position in Marseilles, France Message-ID: Experimental and computational investigations of orthographic processing and reading. Applications are now open for a post-doctoral position at the Laboratoire de Psychologie Cognitive in Marseilles, France, for research investigating orthographic processing during sentence reading. The position is renewable on a yearly basis for up to 5-years, and is part of an ERC-funded research project led by Jonathan Grainger (ERC advanced grant ?Parallel orthographic processing and reading?). The successful applicant will have a PhD in psychology / cognitive science and expertise in computational modeling. She/he will be involved in developing computational models of reading, and setting-up behavioral experiments to test model predictions. Advanced skills in data analysis and scientific writing will also be appreciated. The Laboratoire de Psychologie Cognitive is a thriving research department with more than 20 full-time research scientists and university professors working in various areas of cognitive psychology, and is located at the St. Charles campus of Aix-Marseille University, in central Marseilles. It is part of a large, prestigious interdisciplinary research institute for language, communication, and the brain (ILCB), that brings together psychologists, neuroscientists, linguists, and computer scientists to further our understanding of all aspects of language processing. Applicants should send the names of two referees and a curriculum vitae to: jonathan.grainger at univ-amu.fr -------------- next part -------------- An HTML attachment was scrubbed... URL: From dorien.herremans at gmail.com Fri Nov 10 23:48:13 2017 From: dorien.herremans at gmail.com (Dorien Herremans) Date: Sat, 11 Nov 2017 12:48:13 +0800 Subject: Connectionists: Deadline extension: special issue on Deep Learning for Music and Audio in Springer's NCA (IF: 2.505) Message-ID: *Special Issue on Deep Learning for Music and Audio* in Springer's Neural Computing and Applications (Impact factor: 2.505) *Extended submission deadline: *November 30th *Description and covered topics* There has been tremendous interest in deep learning across many fields of study. Recently, these techniques have gained popularity in the field of music. Projects such as Magenta (Google's Brain Team's music generation project), Jukedeck and others testify to their potential. Following the recent success of the First International Workshop on Deep Learning and Music (DLM2017 ) joint with IJCNN, this special issue aims to offer a venue for publishing the latest state-of-the art in the field of DeepLearning for Music and Audio . While humans can rely on their intuitive understanding of musical patterns and the relationships between them, it remains a challenging task for computers to capture and quantify musical structures. Recently, researchers have attempted to use deep learning models to learn features and relationships that allow us to accomplish tasks in music transcription, audio feature extraction, emotion recognition, music recommendation, and automated music generation. The goal of this special issue is to provide a forum for advancing the state-of-the-art in Deep Learning techniques in the field of Music and Audio. High quality papers are welcomed, including but not limited to topics listed below: - Deep learning for feature extraction and semantic modeling for music and audio - Modeling hierarchical and long term music structures using deep learning - Modeling ambiguity and preference in music - Applications of deep networks for music and audio such as audio transcription, voice separation, music recommendation and etc. - Novel architectures designed for music and audio - Software frameworks and tools for deep learning in music and audio *About the journal* Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems. All items relevant to building practical systems are within its scope, including contributions in the area of applicable neural networks theory, supervised and unsupervised learning methods, algorithms, architectures, performance measures, applied statistics, software simulations, hardware implementations, benchmarks, system engineering and integration and case histories of innovative applications. The Original Articles will be high-quality contributions, representing new and significant research, developments or applications of practical use and value. They will be reviewed by at least two referees. *Guest editors:* Prof. Dr. D. Herremans, Singapore University of Technology and Design Prof. Dr. C.H. Chuan, University of North Florida *Submission deadline:* November 30th Please use the submission system of the journal for your submissions and i*ndicate the special issue during submission *at https://www.springer.com/journ al/521/submission Any *inquiries* can be directed at Prof. Dorien Herremans through dorien_herremans [a] sutd dot edu [] com Join the Deep Learning for Music mailing list at https://groups.google.com/forum/#!forum/icdlm -- Dorien Herremans, PhD Assistant Professor http://dorienherremans.com Singapore University of Technology and Design Information Technology and Design Pillar Office 1.202-17 -------------- next part -------------- An HTML attachment was scrubbed... URL: From serge.thill at his.se Mon Nov 13 11:46:52 2017 From: serge.thill at his.se (Serge Thill) Date: Mon, 13 Nov 2017 16:46:52 +0000 Subject: Connectionists: BMVA Technical meeting : 2nd CfP Cognitively inspired explainable perception-based AI References: <94C63C94-8FB6-41B5-B924-70FEEB83F2B0@his.se> Message-ID: <559FB71D-312D-4461-81F0-F4D9C4290C72@his.se> Dear all, this is a just reminder about the meeting below. The deadline for contribution summaries is approaching (Dec 1). cheers, Serge Begin forwarded message: From: Andrew Gilbert > Subject: Re: BMVA Technical meeting : 2nd CfP Cognitively inspired explainable perception-based AI Date: 19 October 2017 at 16:19:57 BST To: > Reply-To: > BMVA Technical Meeting: Cognitively inspired explainable perception-based AI One Day BMVA symposium in London, UK on Wednesday 7th Feburary 2018 Chairs: Serge Thill, University of Plymouth, Maria Riveiro, University of Sk?vde, Keynote speakers: Alessandra Sciutti, Italian Institute of Technology, Brad Hayes, University of Colorado Boulder & Yiannis Demiris, Imperial College, www.bmva.org/meetings Call for Papers: AI systems are increasingly present in everyday society, from simple computer systems to agents such as autonomous vehicles or social robots. In this context, several researchers have noted that it is critical to understand how human users perceive such systems - in particular, the degree to which they understand how the system works, and what mental models they build of the underlying algorithms. "Explainable AI" thus refers to AI systems that behave or provide the necessary information so that their working becomes comprehensible to the human user. For this meeting, we are interested in AI systems that operate at least somewhat autonomously based on real-world sensory data (in particular, based on machine vision). This includes robotics and autonomous vehicles, but can also cover disembodied systems such as decision support systems. We are particularly interested in contributions that give detailed consideration to the fact that these are AI systems that sense (often through machine vision) the environment, and consider the possible role of understanding human cognitive mechanisms in the design of such systems. Relevant human cognitive mechanisms could include, for example, how humans perceive and interpret information themselves (which may be relevant in the design of explainable information processing by a machine) or how they interact with other intelligent agents (including their expectations on such interactions), which may impose constraints on the design of explainable systems that may be perceived as an intelligent, interactive agent by human users. Submission Deadline: All those interested in presenting at this meeting are invited to submit a summary of their talk at https://goo.gl/forms/OByON7vvlUX0xtDt1 by 1 Dec 2017 [firm deadline]. For queries please contact the organisers: serge.thill at plymouth.ac.uk, maria.riveiro at his.se Registration: Book online at www.bmva.org/meetings ?16 for BMVA Members, ?36 for Non Members, including lunch Thanks for reading Andrew Gilbert -------------- next part -------------- An HTML attachment was scrubbed... URL: From shobeir at gmail.com Mon Nov 13 00:16:36 2017 From: shobeir at gmail.com (Shobeir Fakhraei) Date: Sun, 12 Nov 2017 21:16:36 -0800 Subject: Connectionists: [Final CFP] WSDM HeteroNAM'18 - International Workshop on Heterogeneous Networks Analysis and Mining (Los Angeles, CA) Message-ID: [image: Inline image 1] HeteroNAM 2018: International Workshop on Heterogeneous Networks Analysis and Mining Feb 9, 2018 Los Angeles, California, USA, 2018 (co-located with WSDM?18) http://www.heteronam.org/2018 Submission Deadline: Nov 20, 2017 Keynote Speakers: Nitesh Chawla (University of Notre Dame) Jiawei Han (University of Illinois at Urbana-Champaign) Kristina Lerman (University of Southern California-ISI) Julian McAuley (University of California San Diego) (Additional keynote speakers will be announced soon!) Call for papers: This workshop is a forum for exchanging ideas and methods for heterogeneous networks analysis and mining, developing new common understandings of the problems at hand, sharing of data sets where applicable, and leveraging existing knowledge from different disciplines. The goal is to bring together researchers from academia, industry, and government, to create a forum for discussing recent advances in this area. In doing so, we aim to better understand the overarching principles and the limitations of our current methods and to inspire research on new algorithms and techniques for heterogeneous networks analysis and mining. To reflect the broad scope of work on heterogeneous networks analysis and mining, we encourage submissions that span the spectrum from theoretical analysis to algorithms and implementation, to applications and empirical studies is various domains. The need for analysis and learning methods that go beyond mining simple graphs is emerging in many disciplines and are referred to with different names depending on the type of data augmenting the simple graph. General topics of interest include, but are not limited to: - Heterogeneous Information Networks - Multi-Relational Networks - Signed Networks - Attributed Networks - Aligned Networks - Multigraphs - Multidimensional Networks - Multilayer Networks - Complex Networks - Multimodal Networks Heterogenous networks are becoming the key component in many emerging applications and data-mining and graph-mining related tasks. Some of the related research areas and tasks related to heterogeneous networks include: - Link and relationship strength prediction - Clustering and community detection and formation modeling - Learning to rank in information networks - Similarity measures and relationship extraction - Applications to modeling of weblogs, social media, social networks, medical networks, and the semantic web - Statistical relational learning - Tensor factorization - Network-based classification - Hybrid recommender systems - Information fusion - Network evolution and dynamic networks All papers will be peer reviewed, single-blinded. We welcome many kinds of papers, such as, but not limited to: - Novel research papers - Demo papers - Work-in-progress papers - Visionary papers (white papers) - Appraisal papers of existing methods and tools (e.g., lessons learned) - *Relevant work that has been previously published* - *Work that will be presented at the main conference of WSDM* Authors should clearly indicate in their abstracts the kinds of submissions that the papers belong to, to help reviewers better understand their contributions. Submissions must be in PDF, no more than 8 pages long ? shorter papers are welcome ? and formatted according to the standard double-column ACM Proceedings Style . The accepted papers will be published on the workshop?s website and *will not be considered archival for resubmission purposes.* Authors whose papers are accepted to the workshop will have the opportunity to participate in a spotlight and poster session, and some set may also be chosen for oral presentation. Timeline: *Paper Submission Deadline: Nov 20, 2017 * Author Notification: Dec 14, 2017 Final Version: Jan 1, 2018 Workshop: Feb 9, 2018 Submission Instructions: http://www.heteronam.org/2018 Please send enquiries to *chair at heteronam.org * Organizers: Shobeir Fakhraei (University of Southern California - ISI) Yanen Li (Snap Inc.) Yizhou Sun (University of California Los angeles) Tim Weninger (University of Notre Dame) *Program Committee:* Nesreen Ahmed (Intel Research Labs) Yuxiao Dong (Microsoft Research) Srijan Kumar (Stanford University) Julian McAuley (University of California, San Diego) Fred Morstatter (University of Southern California) Maximilian Nickel (Facebook AI Research) Evangelos Papalexakis (University of California Riverside) Ali Pinar (Sandia National Laboratories) Arti Ramesh (Binghamton University) Neil Shah (Carnegie Mellon University) Chuan Shi (Beijing Uni. of Posts & Telecommunications) Elena Zheleva (University of Illinois at Chicago) To receive updates about the current and future workshops and the Graph Mining community, please join the mailing list: https://groups.google.com/d/forum/mlg-list or follow the twitter account: https://twitter.com/heteronam We look forward to your participation! Best Regards, -- HeteroNAM Organizers *chair at heteronam.org * -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: heteronam-logo-text.png Type: image/png Size: 54624 bytes Desc: not available URL: From tarek.besold at googlemail.com Mon Nov 13 20:21:48 2017 From: tarek.besold at googlemail.com (Tarek R. Besold) Date: Tue, 14 Nov 2017 01:21:48 +0000 Subject: Connectionists: New survey: "Neural-Symbolic Learning and Reasoning: A Survey and Interpretation" (arXiv:1711.03902v1 [cs.AI]) Message-ID: Dear all, we yesterday published a draft of a survey-in-becoming on neural-symbolic learning and reasoning on arXiv: https://arxiv.org/abs/1711.03902 The current version is still lagging (at least) a year behind the latest papers relevant for the overarching theme of integrating learning and reasoning/signals and symbols; we are working towards closing this gap. Nonetheless, I hope that already now the survey can be of use to some people either as entry point to the topic, or as reference document. Also, we are very happy about any pointers to work which should definitely be included in a future version ? just let me know, and we will see how and where to fit it in. Cheers, Tarek. --- Tarek R. Besold, PhD Lecturer in Data Science Department of Computer Science City, University of London Email: Tarek-R.Besold at city.ac.uk WWW: http://www.cat-ai.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From ahmedhalimo at gmail.com Mon Nov 13 20:26:09 2017 From: ahmedhalimo at gmail.com (Ahmed Moustafa) Date: Tue, 14 Nov 2017 12:26:09 +1100 Subject: Connectionists: A new comprehensive book on Computational Neuroscience Message-ID: Dear all, I have been lucky enough to work with various computational modeling researchers on this book, which is finally out. https://www.amazon.com/Computational-Models-Brain-Behavior-Moustafa/dp/1119159067 please, let me know if you have any questions about it Best, Ahmed -------------- next part -------------- An HTML attachment was scrubbed... URL: From t.heskes at science.ru.nl Mon Nov 13 17:54:02 2017 From: t.heskes at science.ru.nl (Tom Heskes) Date: Mon, 13 Nov 2017 23:54:02 +0100 Subject: Connectionists: Machine Learning workshop on Dark Matter Message-ID: [with apologies for cross-posting; a few places are still available] Accelerating the Search for Dark Matter with Machine Learning From Monday 15 January through Friday 19 January 2018 Lorentz Center@ Oort ? Leiden, The Netherlands Scientific Topic In this workshop we aim to explore, and to encourage, the utilization of state-of-the-art machine learning algorithms for research in dark matter physics and astronomy. Our objective is to accelerate the identification of Dark Matter with a multidisciplinary approach: The researchers coming to this workshop bring together expertise in experimental and theoretical particle physics, astrophysics, astronomy, statistics and Machine Learning. The workshop is planned to be a Kickoff meeting to generate a new open research community. We plan a whitepaper, follow-up workshops, a web page and a mailing list for the DM-ML community. Workshop Format Lorentz Workshops@ Oort are scientific meetings for small groups of up to 55 participants, including both senior and junior scientists. Lorentz Center meetings dedicate a considerable amount of time to discussion sessions, thus stimulating an interactive atmosphere and encouraging collaborations between participants. This format typically generates extensive debates and enables significant progress to be made within the research topic of the meeting. Lorentz Center Facilities The venue Lorentz Center@ Oort, located at the Faculty of Science campus of Leiden University, the Netherlands. The Lorentz Center provides each participant with office space and wireless internet access (LINUX and Windows). Lorentz Center also provides various practical services for the participants, such as arranging accommodations at the nearby hotel ?Van der Valk Hotel Leiden? at a special rate (? 85 per night including breakfast and taxes), visa assistance and bike rental. For further information, please refer to our website: www.lorentzcenter.nl. Costs and Refunds Lorentz Center does not charge registration fees. In addition, Lorentz Center hosts a welcome reception and a workshop dinner, both free of charge. On request some participants can be provided with free accommodation at the hotel ?Van der Valk Hotel Leiden? courtesy of Lorentz Center and with reimbursement of travel expenses. Travel expenses will be transferred after the workshop, upon presentation of your ticket or travel receipts. If you need a contribution to your expenses, please contact the scientific organizers. You are cordially invited to bring the workshop to the attention of bright junior scientist in your environment. As the workshop is built on interaction and discussion, we encourage you to participate for the whole workshop week. Registration by November 17 via the workshop webpage: http://www.lorentzcenter.nl/lc/web/2018/920/info.php3?wsid=920&venue=Oort Developing agenda: https://indico.cern.ch/event/664842/ Due to a limit of 60 participants the approval to the workshop is at the discretion of the organizers. You will be informed on their admission by the end of November 2017 at the latest. Organisers: Tom Heskes (Radboud University), Gianfranco Bertone (UvA), Francesca Calore (CNRS), Sascha Caron (Radboud University and Nikhef) and Roberto Ruiz de Austri (IFIC Valencia) From robert.jenssen at uit.no Tue Nov 14 02:42:08 2017 From: robert.jenssen at uit.no (Robert Jenssen) Date: Tue, 14 Nov 2017 07:42:08 +0000 Subject: Connectionists: 1st Northern Lights Deep Learning Workshop In-Reply-To: <1502093829881.59265@uit.no> References: <1502093829881.59265@uit.no> Message-ID: <1510645313264.70793@uit.no> Call for contributions: Deadline 20th Nov. for the 1st Northern Lights Deep Learning Workshop 10-11 January 2018, Tromso, "North Pole", Norway. Please see nldl2018.org for more info. Registrations will soon open soon.? Robert Jenssen Michael Kampffmeyer Arnt-Borre Salberg --- Robert Jenssen UiT Machine Learning Group http://site.uit.no/ml Department of Physics and Technology University of Tromso (UiT) - The Arctic University of Norway -------------- next part -------------- An HTML attachment was scrubbed... URL: From SchockaertS1 at cardiff.ac.uk Tue Nov 14 07:32:32 2017 From: SchockaertS1 at cardiff.ac.uk (Steven Schockaert) Date: Tue, 14 Nov 2017 12:32:32 +0000 Subject: Connectionists: Postdoc positions on learning with interpretable vector space embeddings Message-ID: <3BE97827-C877-43FE-87D2-4891B7F12C9C@cardiff.ac.uk> Start date: 1 January 2018 (or as soon as possible thereafter) Closing date: 10 December 2017 Duration: 24 months Keywords: Knowledge graphs, conceptual spaces, vector space embeddings, statistical learning, neural networks Applications are invited for two postdoctoral research posts at Cardiff University?s School of Computer Science & Informatics in the context of the ERC funded project FLEXILOG. The overall aims of this project are (i) to learn interpretable vector space embeddings (or conceptual spaces) from a variety of structured and unstructured information sources, and (ii) to exploit these embeddings for improving statistical and symbolic inference from imperfect data. More information about FLEXILOG can be found on the project website: http://www.cs.cf.ac.uk/flexilog/ Specifically, the aim of these posts will be to contribute to one or more of the following: (i) to develop methods for statistical reasoning from sparse relational data, which exploit vector space representations to impose cognitively inspired forms of regularization (e.g. the fact that concepts tend to correspond to convex regions). (ii) to develop methods for learning modular and interpretable vector space representations of events, which can be used to predict how events will impact the actors involved (and the entities related to them), as well as the likelihood of related future events. (iii) to evaluate these methods in applications such as zero-shot learning, textual entailment, reading comprehension, automated knowledge base completion, and entity retrieval. Successful candidates are expected to have excellent programming skills, as well as a strong background in natural language processing, machine learning, or knowledge representation. Cardiff University is a member of the Russell Group of research universities, and was ranked 5th in the UK based on the quality of research in the 2014 Research Evaluation Framework. The university has a successful School of Computer Science & Informatics with an international reputation for its teaching and research activities. Cardiff is a strong and vibrant capital city with good transportation links and an excellent range of housing available. More information: For more details about the positions, please contact Steven Schockaert (SchockaertS1 at cardiff.ac.uk). For instructions on how to apply, please go to www.cardiff.ac.uk/jobs and search for job 6522BR. Please note the requirement to evidence all essential criteria in the supporting statement. -------------- next part -------------- An HTML attachment was scrubbed... URL: From d.terhorst at fz-juelich.de Tue Nov 14 09:13:32 2017 From: d.terhorst at fz-juelich.de (Dennis Terhorst) Date: Tue, 14 Nov 2017 15:13:32 +0100 Subject: Connectionists: NEST Conference 2017 --- Register NOW! Message-ID: Dear all! Coming up mid of December the community of NEST users and developers will meet to discuss neuroscientific work with NEST and the status and future of simulation technology on the NEST Conference 2017 to be held on 19/20 December 2017 (Tuesday/Wednesday, lunch to lunch) at Haus Overbach in Barmen near J?lich, Germany. After our very successful and stimulating meeting in Karlsruhe last November, we are greatly looking forward to 24 hours filled with presentations and discussions of NEST applications to computational neuroscience and neurorobotics projects and NEST technology development. You are cordially invited to contribute to the program with your contribution! We are grateful to the Human Brain Project Outreach Programme and Education Programme for financial support. Important deadlines: - 19 November 2017: Extended deadline for submission of contribution - 26 November 2017: Extended deadline for registrations For details, contribution submission and registration, please see https://indico-jsc.fz-juelich.de/event/52/overview We are looking forward to seeing you all in December! best, Dennis Terhorst -- Dipl.-Phys. Dennis Terhorst Coordinator Software Development Institute of Neuroscience and Medicine (INM-6) Computational and Systems Neuroscience & Theoretical Neuroscience, Institute for Advanced Simulation (IAS-6) J?lich Research Centre, Member of the Helmholz Association and JARA 52425 J?lich, Germany Building 15.22 Room 4004 Phone +49 2461 61-85062 Fax +49 2461 61- 9460 d.terhorst at fz-juelich.de -------------- next part -------------- A non-text attachment was scrubbed... Name: smime.p7s Type: application/pkcs7-signature Size: 5110 bytes Desc: S/MIME Cryptographic Signature URL: From brody at princeton.edu Tue Nov 14 15:41:30 2017 From: brody at princeton.edu (Carlos Brody) Date: Tue, 14 Nov 2017 15:41:30 -0500 Subject: Connectionists: Princeton Intensive Summer School in Neuroscience Message-ID: <80D63321-86C7-4F5C-8A05-128499DAE522@princeton.edu> ** Princeton Intensive Summer School in Neuroscience ** We want to bring to your attention an intensive 4-week summer course, Cellular, Computational and Cognitive Neuroscience (C3N), designed to introduce physicists, mathematicians, engineers and computer scientists to the major questions and techniques of modern neuroscience. The course has a special emphasis, in both lecture and laboratory components, on modern recording and analysis methods, ranging from large scale electrode and optical recording (and optogenetic stimulation) to mathematical analysis of neural dynamics within the datasets produced by these methods. The course and application are described in detail at http://C3N.princeton.edu . Senior graduate students or postdoctoral fellows are particularly appropriate candidates for the C3N course. Grants from the NIMH and the Burroughs Wellcome Foundation allow us to meet the full financial needs of all admitted students. The application deadline is Feb. 1 2018. http://C3N.princeton.edu David Tank, Michael Berry and Alan Gelperin, Princeton Neuroscience Institute -------------- next part -------------- An HTML attachment was scrubbed... URL: From benoit.frenay at unamur.be Wed Nov 15 04:02:11 2017 From: benoit.frenay at unamur.be (Benoit Frenay) Date: Wed, 15 Nov 2017 10:02:11 +0100 Subject: Connectionists: [New deadline] Interaction and User Integration in ML for Infovis at ESANN'18 Message-ID: <4c96bf3f-a6a7-8760-e6ee-0ab2d27db19c@unamur.be> [Apologies if you receive multiple copies of this CFP] The deadline has been extended to _*29 November 2017*_. Call for papers: ?special session on "Interaction and User Integration in Machine Learning for Information Visualisation" at ESANN 2018 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). 25-27 April 2018, Bruges, Belgium -http://www.esann.org DESCRIPTION: Many methods have been developed in machine learning (ML) for information visualisation (infovis).? For example, PCA, MDS, t-SNE and improvements are standard tools to reduce the dimensionality of high dimensional datasets for visualisation purposes.? However, multiple other means are regularly used in the field of infovis when tackling datasets with high dimensionality. Letting the user manipulate the visualisation is one of these means, either through selection, navigation or filtering. Introducing manipulation of the visualisation also integrates the user as a core aspect of a given system.? In the context of machine learning, beyond the informational and exploratory use of infovis, users' feedback can for example be highly informational to drive the dimensionality reduction process. This special session of the ESANN conference is a followup of the special session on "Information Visualisation and Machine Learning: Techniques, Validation and Integration" at ESANN 2016.? It aims to gather researchers that integrate users in the core of ML methods for infovis. New algorithms and frameworks are welcome, as well as experimental use cases that bring new insight in the integration of interaction and user integration in ML for infovis.? This special session aims to provide practitioners from both communities a common forum of discussion where issues at the crossroads of machine learning and information visualisation could be discussed. Topics of interest include, but are not limited to: * ??? supervised and semi-supervised machine learning and infovis * ??? unsupervised ML (clustering, dimension reduction) * ??? user feedback on metaparameters * ??? new visual paradigms for machine learning * ??? interaction techniques for infovis with/of machine learning * ??? user and device adaptivity for visual analytics * ??? warm restart and dedicated optimization techniques * ??? scalability * ??? applications in industry, agriculture, medicine, biology, etc. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided inhttp://www.elen.ucl.ac.be/esann/index.php?pg=submission. ?Each paper will undergo a peer reviewing process for its acceptance. ?Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Paper submission deadline : *29 November 2017* 20 November 2017 Notification of acceptance : 31 January 2018 The ESANN 2014 conference : 25-27 April 2018 SPECIAL SESSION ORGANISERS: Prof. Bruno Dumas Universit? de Namur, Belgium E-mail: bruno.dumas at unamur.be Website: http://directory.unamur.be/staff/bdumas Phone: +32 81 72 49 75 Prof. Beno?t Fr?nay Universit? de Namur, Belgium E-mail: benoit.frenay at unamur.be Website:http://bfrenay.wordpress.com Phone: +32 81 72 49 76 Prof. John Lee Universit? catholique de Louvain, Belgium E-mail: john.lee at uclouvain.be Website:https://mlg.info.ucl.ac.be/Members/JohnLee Phone: +32 2 764 95 28 -- Beno?t FR?NAY Associate Professor Faculty of Computer Science T. +32 (0)81 724 976 (secr. 725 252) F. +32 (0)81 724 967 benoit.frenay at unamur.be Universit? de Namur ASBL Rue de Bruxelles 61 - 5000 Namur Let?s respect the environment together. Only print this message if necessary! -------------- next part -------------- An HTML attachment was scrubbed... URL: From smartstart at fz-juelich.de Wed Nov 15 04:59:00 2017 From: smartstart at fz-juelich.de (Smart Start Coordination Office) Date: Wed, 15 Nov 2017 10:59:00 +0100 Subject: Connectionists: Call for SMARTSTART Applications Message-ID: <9f96cf3e-2bc2-2224-061f-de84a5f02d75@fz-juelich.de> Ready for a SMARTSTART into Computational Neuroscience? We invite first and second-year Master students with a background in related fields to apply to our joint training program SMARTSTART. The program aims at complementing previous studies with concepts, theories and techniques of Computational Neuroscience. SMARTSTART consists of two programs. Both of them last one year each and take place at numerous locations of the Bernstein Network and further locations throughout Germany. SMARTSTART 1 provides financial support to then second-year Master students, allowing them to attend supplementary courses and training visits at participating institutions. Students will receive an experienced faculty mentor who will advise and guide them at this educational stage. SMARTSTART 2 provides fully funded positions for pre-PhD students. At the start of the program, these students will have already obtained their Master?s degree and are in the process of selecting a PhD project. SMARTSTART 2 allows them to elaborate their own PhD proposal as a collaborative project between two labs. This comprises exchange visits as well as voluntary attendance of lectures and courses offered by participating institutions. Both SMARTSTART programs will commence the next round in the winter term 2018/19. The Deadline for application is Wednesday, February 28, 2018. More information can be found on our website: www.smartstart-compneuro.de Best regards, Kathrin Hebert -- Coordination Office Smart Start - Joint Training Program in Computational Neuroscience Bernstein Network Computational Neuroscience | Bernstein Coordination Site (BCOS) Branch Office of the Forschungszentrum J?lich at the University of Freiburg Hansastr. 9A | 79104 Freiburg, Germany phone: (+49) 0761 203 9593 mail: smartstart at fz-juelich.de web: www.nncn.de Twitter: NNCN_Germany YouTube: Bernstein TV Facebook: Bernstein Network Computational Neuroscience, Germany LinkedIn: Bernstein Network Computational Neuroscience, Germany ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ Forschungszentrum Juelich GmbH 52425 Juelich Sitz der Gesellschaft: Juelich Eingetragen im Handelsregister des Amtsgerichts Dueren Nr. HR B 3498 Vorsitzender des Aufsichtsrats: MinDir Dr. Karl Eugen Huthmacher Geschaeftsfuehrung: Prof. Dr.-Ing. Wolfgang Marquardt (Vorsitzender), Karsten Beneke (stellv. Vorsitzender), Prof. Dr.-Ing. Harald Bolt, Prof. Dr. Sebastian M. Schmidt ------------------------------------------------------------------------------------------------ ------------------------------------------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From luca.oneto at unige.it Wed Nov 15 09:13:34 2017 From: luca.oneto at unige.it (Luca Oneto) Date: Wed, 15 Nov 2017 15:13:34 +0100 Subject: Connectionists: ESANN 2018 SS Deadline Extension - Emerging trends in machine learning: beyond conventional methods and data Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Emerging trends in machine learning: beyond conventional methods and data" at ESANN 2018 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). 25-27 April 2018, Bruges, Belgium - http://www.esann.org DESCRIPTION: Recently, new promising theoretical results, techniques, and methodologies have attracted the attention of many researchers and have allowed to broaden the range of applications in which machine learning can be effectively applied in order to extract useful and actionable information from the huge amount of heterogeneous data produced everyday by an increasingly digital world. Examples of these methods and problems are: - Learning under privacy and anonymity constraints - Learning from structured, semi-structured, multi-modal (heterogeneous) data - Constructive machine learning, e.g. generative models and structured output learning - Reliable machine learning - Learning to learn, e.g. lifelong learning and learning the loss - Mixing deep and structured learning, e.g. mixture of wide and deep models - Semantics-enabled recommender systems - Reproducibility and interpretability in machine learning - Human in the loop - Adversarial learning The focus of this special session is to attract both solid contributions or preliminary results which show the potentiality and the limitations of new ideas, refinements, or contaminations between the different fields of machine learning and other fields of research in solving real world problems. Both theoretical and practical results are welcome to our special session. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided in https://www.elen.ucl.ac.be/esann /index.php?pg=submission. Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Submission of papers: *29 November 2017* Notification of acceptance: 31 January 2018 ESANN conference: 25-27 April 2018 SPECIAL SESSION ORGANISERS Luca Oneto , University of Genoa (Italy) Nicol? Navarin , University of Padua (Italy) Michele Donini , Istituto Italiano di Tecnologia (Italy) Davide Anguita , University of Genoa (Italy) ------------------------------------------------------------ ----------------------- Luca Oneto, PhD University of Genoa web: www.lucaoneto.com DIBRIS Department e-mail: Luca.Oneto at unige.it SmartLab Laboratory e-mail: Luca.Oneto at gmail.com Via Opera Pia 11a Fax: +39-010-3532897 <+39%20010%20353%202897> 16145 Genoa ITALY Phone: +39-010-3532192 <+39%20010%20353%202192> www.smartlab.ws ------------------------------------------------------------ ----------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From bazhenov at salk.edu Wed Nov 15 13:24:09 2017 From: bazhenov at salk.edu (Maxim Bazhenov) Date: Wed, 15 Nov 2017 10:24:09 -0800 Subject: Connectionists: Postdoctoral position in computational neuroscience and machine learning Message-ID: <66f45432-6776-42a2-f99a-153ab4a6f5de@salk.edu> Applications are invited for a post-doctoral research position in the laboratory of Dr. Maxim Bazhenov at the University of California, San Diego to develop neuroscience inspired machine learning algorithms capable of continual learning and adapting to the novel situations and contexts.This project involves close collaboration with the experimental laboratory of Dr. Bruce McNaughton (UC Irvine). The ultimate goal of the work is to advance the knowledge of how human and animal brains learn from experience and apply these principles to the artificial systems to enable continuous learning without catastrophic forgetting. The successful candidate will collaborate with a team of researchers to design neural network models of dynamic interactions between the hippocampus and neocortex during learning and memory consolidation based on experimental data. These models will be used to derive learning principles that can be combined with advances in artificial intelligence and machine learning. An ideal candidate should have experience in computational/theoretical neuroscience and a basic knowledge of machine learning, or, alternatively, experience in machine learning algorithms and some basic knowledge ofneuroscience. Experience with hierarchical learning, reinforcement learning, and/or goal-directed decision-making would be particularly helpful. The University of California offers excellent benefits. Salary is based on research experience. Applicants should send a brief statement of research interests, a CV and the names of three references to Maxim Bazhenov at mbazhenov at ucsd.edu -- Maxim Bazhenov, Ph.D. Professor, Department of Medicine, Neurosciences Graduate Program, UCSD, School of Medicine http://www.bazhlab.ucsd.edu/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From Tingting.Mu at manchester.ac.uk Wed Nov 15 11:55:11 2017 From: Tingting.Mu at manchester.ac.uk (Tingting Mu) Date: Wed, 15 Nov 2017 16:55:11 +0000 Subject: Connectionists: Invitation to VQA challenge Message-ID: <8C1BAF6A-0663-40E7-ACAF-18087449DF15@manchester.ac.uk> Dear All, We are very happy to invite you to the "Question Answering Mediated by Visual Clues and Knowledge Graphs? challenge, LYON, FRANCE (23 - 27 April 2018). Please see information below. Question Answering Mediated by Visual Clues and Knowledge Graphs WWW 2018 LYON, FRANCE (23 - 27 April 2018) Website: https://visual-question-answering-challenge.github.io/ Summary: This challenge focuses on the use of semantic representation methods to support Visual Question Answering: given a large image collection, find a set of images matching natural language queries. The task will support advancing the state-of-the-art in Visual Question Answering by focusing on methods which explore the interplay between contemporary machine learning techniques, semantic representation and reasoning mechanisms. Topics of interest for the challenge include (but are not restricted to): - Visual Question Answering (QA) architectures and techniques. - Representation learning / Semantic representation models for Visual QA. - Machine learning methods for Visual QA. - Zero and one-shot learning methods. - Use of Web Data and Knowledge Graphs to support Visual QA. - Linguistic resources and datasets. - New evaluation paradigms. Timeline: * Publication of the training data: December 1st , 2017. * Challenge papers submission deadline: February 4th, 2018. * Challenge papers acceptance notification: February 14th, 2018. * Challenge test data published and submission of results: February 14th, 2018. Paper Submission: The Web Conference Challenges is an official track of the conference. We request from participants to provide, in addition to their participation to the challenge, a paper describing the proposed solution and, when relevant, self-assessments related to the defined criteria for evaluation. These papers will be published in the official satellite proceedings of the conference. Organizers: Fabricio Faria, Federal University of Rio de Janeiro Andre Freitas, University of Manchester Ricardo Usbeck, Paderborn University Tingting Mu, University of Manchester Alessio Sarullo, University of Manchester -------------- next part -------------- An HTML attachment was scrubbed... URL: From michel.verleysen at uclouvain.be Wed Nov 15 15:20:37 2017 From: michel.verleysen at uclouvain.be (Michel Verleysen) Date: Wed, 15 Nov 2017 20:20:37 +0000 Subject: Connectionists: ESANN 2018 deadline extension Message-ID: <7d56f6994e11493e9466466a37858773@ucl-mbx06.OASIS.UCLOUVAIN.BE> ====================================================== ESANN 2018 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges (Belgium) - April 25-26-27, 2018 http://www.esann.org/ *** Submission deadline extension *** ====================================================== Due to numerous requests the deadline to submit papers to the ESANN 2018 conference has been extended to November 29, 2017. Please note that no further extension will be given. Looking forward to seeing you at ESANN 2018, The organizing committee. [http://www.uclouvain.be/cps/ucl/doc/ac-arec/images/logo-signature.png] Michel Verleysen Professor ICTEAM institute Place du Levant, 3 box L5.03.02 B-1348-Louvain-la-Neuve michel.verleysen at uclouvain.be T?l. +32 10 47 25 51 - Fax +32 10 47 25 98 perso.uclouvain.be/michel.verleysen -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.png Type: image/png Size: 3010 bytes Desc: image002.png URL: From m.biehl at rug.nl Wed Nov 15 16:31:58 2017 From: m.biehl at rug.nl (Michael Biehl) Date: Wed, 15 Nov 2017 22:31:58 +0100 Subject: Connectionists: Deadline extended: Special Session on Astroinformatics at ESANN 2018 Message-ID: *Deadline extension: * *Special Session at ESANN 2018* 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning Bruges/Belgium, April 25-27 2017. *Machine Learning and Data Analysis in Astroinformatics* *Organized by M. Biehl, K. Bunte (University of Groningen, The Netherlands), **G. Longo (University of Naples, Italy), P. Tino (University of Birmingham, UK) * The ever-growing amount of data which becomes available in many domains clearly requires the development of efficient methods for data mining and analysis. These challenges occur in a variety of areas including societal issues, business and fundamental scientific research. Astronomy continuous to be at the forefront of this development: Modern observational techniques provide enormous amounts of data, which have to be processed efficiently. The development of methods for their reliable acquisition and analysis has immediate impact on other areas including commercial applications, data security, environmental monitoring etc. This special session is meant to attract researchers who develop, investigate or apply methods of neural networks, machine learning and data analysis in the context of astronomical data. Potential topics include, but are not limited to - big data mining in astronomy - the processing of astronomical images - filtering techniques for streams of astronomical data - outlier and novelty detection in observational data - classification or clustering of celestial objects - simulation of astrophysical models and related - inference problems - the analysis of heterogeneous data stemming from - various sources or technical platforms Important dates: Submission of papers: *27 November 2017* Notification of acceptance: 31 January 2018 ESANN conference: 25 - 27 April 2018 More information can be found at http://www.elen.ucl.ac.be/esann/index.php?pg=specsess#astroinformatics http ://www.esann.org -- ---------------------------------------------------------- Prof. Dr. Michael Biehl Johann Bernoulli Institute for Mathematics and Computer Science P.O. Box 407, 9700 AK Groningen The Netherlands Tel. +31 50 363 3997 www.cs.rug.nl/~biehl m.biehl at rug.nl -------------- next part -------------- An HTML attachment was scrubbed... URL: From yao2107 at columbia.edu Wed Nov 15 16:20:55 2017 From: yao2107 at columbia.edu (Allison Ong) Date: Wed, 15 Nov 2017 16:20:55 -0500 Subject: Connectionists: Deadline Approaching: Theoretical/Statistical Neuroscience Faculty Openings at Columbia Message-ID: Dear Colleague, This is a friendly reminder that *Dec 1, 2017 *is the deadline for Columbia's search for *two faculty positions in Theoretical and Statistical Neuroscience.* We would appreciate it if you could forward the information below or the flier attached to any interested candidates. The link to apply is: academicjobs.columbia.edu/ applicants/Central?quickFind=65051 Thanks and Best Wishes, Larry Abbott and Liam Paninski *Two Junior Faculty Position in Theoretical / Statistical Neuroscience* The Department of Neuroscience, the Department of Statistics, and the Mortimer B. Zuckerman Mind Brain Behavior Institute at Columbia University invite applications for two tenure-track positions at the Assistant or Associate Professor level, to begin in 2018. One position will focus on theoretical neuroscience with an appointment in the Department of Neuroscience. The other position will focus on the application of statistics to neuroscience with an appointment in the Department of Statistics. Both positions will include appointments as well as office and laboratory space in the Center for Theoretical Neuroscience and the Grossman Center of the Statistics of Mind within the Mortimer B. Zuckerman Mind Brain Behavior Institute housed in the Jerome L. Greene Science Center at Columbia. The Zuckerman Institute brings together scientists from diverse backgrounds whose research focuses on brain function, wiring, and development. We are seeking dynamic scientists interested in exploiting this multidisciplinary environment by interacting with Zuckerman Institute faculty as well as with others in the Columbia neuroscience, biological sciences, physical sciences, statistics, and machine learning communities, including the Data Science Institute. Zuckerman Institute faculty will function as full members of their home departments: tenure will be granted by the home department and faculty will contribute to teaching in their home departments and the Zuckerman Institute. Candidates will be expected to show expertise and an ability to lead a research program in theoretical and/or statistical neuroscience. Applicants are expected to have a strong record of scientific achievement and to demonstrate the ability to engage in innovative research and teaching. Applicants should hold a PhD in neuroscience, statistics, or a related area. Applications should be submitted through this link: academicjobs.columbia.edu/applicants/Central?quickFind=65051 The following documents should be uploaded with your application: cover letter, CV, research plan, teaching statement, three letters of reference or a listing of at least three references that can be contacted, and the inclusion of one or two publications. Women and minorities are strongly encouraged to apply. We will start to evaluate applications on December 1, 2017. Columbia University is an Equal Opportunity/Affirmative Action employer --Race/Gender/Disability/Veteran. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Columbia Theoretical Statistical Neuroscience Jr Faculty Positions.pdf Type: application/pdf Size: 65534 bytes Desc: not available URL: From yael at Princeton.EDU Wed Nov 15 17:13:19 2017 From: yael at Princeton.EDU (Yael Niv) Date: Wed, 15 Nov 2017 22:13:19 +0000 Subject: Connectionists: Graduate studies at the Princeton Neuroscience Institute - deadline Nov 27! In-Reply-To: <5B9E8D93-0F21-41F4-ABAB-639B5A13053B@princeton.edu> References: <5B9E8D93-0F21-41F4-ABAB-639B5A13053B@princeton.edu> Message-ID: <298DD88B-0EF8-4CF5-A67A-41ED8E9AC787@princeton.edu> The Graduate Program in Neuroscience at Princeton University offers a unique and intensive program of study spanning molecular, cellular, systems and cognitive neuroscience, followed by advanced research in a world-class Princeton laboratory. We seek highly motivated and creative students to join us in our efforts to understand the brain. A listing of faculty affiliated with the program can be found online at http://pni.princeton.edu/faculty-research/faculty-research-summary, and below. Our doctoral program is flexible and individually-tailored, and we encourage students to pursue research with more than one faculty and across departmental boundaries. Applications for entry in the Fall of 2017 are now being accepted, with a deadline of November 27 (note that this is earlier than usual). For details, including contact information, please visit www.princeton.edu/neuroscience. Applicants from Puerto Rico or the U.S. Virgin Islands who have questions about their ability to meet all admission requirements by the deadline should reach out to gs at princeton.edu. Applicants experiencing financial hardship can apply for a waiver of the application fee. Michael Berry - Neural computation in the visual system William Bialek - Interface between physics and biology Lisa Boulanger - Neuro-immune interactions in brain health and disease Carlos Brody - Quantitative and behavioral neurophysiology Tim Buschman - Neural dynamics of cognitive control Jonathan Cohen - Neural bases of cognitive control Nathaniel Daw - Reward, learning and decision making, computational psychiatry Lynn Enquist - Neurovirology Annegret Falkner - Neural circuits for social behaviors Liz Gavis - mRNA localization and translational control in dendrite morphogenesis Alan Gelperin - Learning, memory and olfaction Asif Ghazanfar - Neuromechanics and communication Elizabeth Gould - Neurogenesis and hippocampal function Michael Graziano - Brain basis of consciousness Uri Hasson - Hierarchy of processing timescales and brain-to-brain communication Sabine Kastner - Neural basis for visual attention, comparative primate electrophysiology Andrew Leifer - Whole-brain neural dynamics underlying behavior Carolyn McBride - Molecular and neural basis of behavioral evolution Mala Murthy - Neural mechanism of sensorimotor integration and behavior Coleen Murphy - Molecular mechanisms of aging Yael Niv - Learning & decision making, computational psychiatry Ken Norman - Cognitive neuroscience of learning and memory Jonathan Pillow - Neural information processing, machine learning, and statistical modeling of neural data Sebastian Seung - Structure and function of neural circuits Joshua Shaevitz - Neural and behavioral dynamics in simple organisms David Tank - Neural circuit dynamics Jordan Taylor - Motor control and learning Alexander Todorov - Cognitive neuroscience of social cognition and behavior Samuel Wang - Dynamics and learning in neural circuits Ilana Witten - Neural circuits underlying reward -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: PNI Brochure 2017.pdf Type: application/pdf Size: 6861787 bytes Desc: PNI Brochure 2017.pdf URL: From vcutsuridis at gmail.com Thu Nov 16 06:49:26 2017 From: vcutsuridis at gmail.com (Vassilis Cutsuridis) Date: Thu, 16 Nov 2017 11:49:26 +0000 Subject: Connectionists: Neural models of antisaccade performance in schizophrenia and OCD Message-ID: Dear colleagues, I would like to bring to your attention two papers of mine on neural modelling of antisaccade performance of healthy controls, schizophrenia and obsessive-compulsive disorder (OCD) patients. Experimental studies show deficits in antisaccade performance of schizophrenia and OCD patients : increased variability in saccade response times and increased error rates. In collaboration with two psychiatric research groups from Germany and Greece, the mechanisms that give rise to these antisaccade performance deficits were investigated. This research has led a number of important discoveries on what goes wrong in the decision making processes in psychiatric diseases: - Why is the antisaccade performance of schizophrenia and OCD patients so poor? - Why are latencies more variable and errors greater in schizophrenia and OCD patients than in controls? - Is the poor performance of schizophrenia and OCD suffering patients performing the antisaccade task is due to a deficit in the top-down inhibitory control of the erroneous response? - Is there a need for an additional STOP decision signal (inhibitory and top-down in nature) to suppress (or inhibit) the erroneous response in the antisaccade task when the correct antisaccade has been expressed first? Both papers can be downloaded from here: *Cutsuridis V. (2017). A Neural Accumulator Model of Antisaccade Performance of Healthy Controls and Obsessive-Compulsive Disorder Patients. In M. K. vanVugt, A. P. Banks, & W. G. Kennedy (Eds.). Proceedings of the 15th International Conference on Cognitive Modeling. Coventry, United Kingdom: University of Warwick. * * * *Cutsuridis V*, Kumari V, Ettinger, U. (2014). Antisaccade performance in schizophrenia: A Neural Model of Decision Making in the Superior Colliculus. *Front. Neurosci.*, 8:13. Comments, questions, etc are most welcome. Best regards, Vassilis --- Dr Vassilis Cutsuridis Senior Lecturer in Computer Science School of Computer Science University of Lincoln Lincoln UK Tel: +44 (0) 1522 83 5701 Email: vcutsuridis at lincoln.ac.uk Web: http://staff.lincoln.ac.uk/vcutsuridis Personal web: http://www.vassiliscutsuridis.com/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From Pavis at iit.it Thu Nov 16 09:19:59 2017 From: Pavis at iit.it (Pavis) Date: Thu, 16 Nov 2017 14:19:59 +0000 Subject: Connectionists: Call for Postdoctoral position in Machine Learning for biomedical image analysis - 74477 In-Reply-To: <0E09F354EB71FC40A4D51EE54D8A9C88BDF911A0@IITMXWGE015.iit.local> References: <0E09F354EB71FC40A4D51EE54D8A9C88BDF911A0@IITMXWGE015.iit.local> Message-ID: <0E09F354EB71FC40A4D51EE54D8A9C88BDF911DD@IITMXWGE015.iit.local> Postdoctoral position in Machine Learning for biomedical image analysis BC 74477 Workplace: Genova, Italy Expires on December 15th, 2017 The Pattern Analysis and Computer Vision (PAVIS, http://pavis.iit.it/) department and the Visual Geometry and Modelling (VGM, http://vgm.iit.it/) Research Line at Istituto Italiano di Tecnologia are looking for a highly motivated full-time post-doc (1 year duration) to work on a biomedical imaging project related to blood smears image analysis. The candidate will consolidate PAVIS/VGM expertise in the research area of image analysis for cells detection, segmentation and classification. The research theme is related to the development of a highly efficient medical application in collaboration with an industrial partner. The focus will be on the creation of a software tool inspecting stained blood films for the detection and classification of blood white cells based on their morphological characterization. This implies the development of ad-hoc algorithms for detection and classification of cells based on machine learning methods and in particular exploiting deep learning state-of-the-art models. The inspection problem will also require the investigation of standard classification approaches based on visual-feature, exploiting therefore feature extraction and selection methods. The ideal candidates for this position has a Ph.D. in machine learning, computer vision or related areas, and research experience and qualification should be within the following subjects: image analysis, cells detection and segmentation, machine learning, deep learning, feature extraction. Strong programming skill are highly required, preferably with good knowledge of Matlab, Python and C/C++ languages. Evidence of high quality research on the above specified areas in the form of published papers in top conferences/journals and/or patents will be duly considered. Salary will be commensurate to qualification and experience and in line with international standard. Further details and informal enquires can be made by email to pavis at iit.it quoting BIO-PD 74477 as reference number in the subject. Please send your application, including a curriculum vitae (possibly with a pdf of your most representative publications) a research statement also describing your previous research experience and outlining its relevance to the call topics and the names of 2 referees, to pavis at iit.it, quoting ?BIO-PD 74477? as reference number. This call will remain open and applications will be reviewed until the position is filled, but for full consideration please apply by December 15, 2017. Please note that this position is contingent on budget approval. Istituto Italiano di Tecnologia (IIT), with its headquarters in Genova, Italy, is a non-profit institution with the primary goal of creating and disseminating scientific knowledge and strengthening Italy?s technological competitiveness. The institute offers state-of-the-art equipment and a top-level interdisciplinary research environment focused on robotics and computer vision, neuroscience, drug discovery, nanoscience and technology. In order to comply with the Italian law (art. 23 of Privacy Law of the Italian Legislative Decree n. 196/03), we have to kindly ask the candidate to give his/her consent to allow IIT to process his/her personal data. We inform you that the information you provide will be used solely for the purpose of assessing your professional profile to meet the requirements of Istituto Italiano di Tecnologia. Your data will be processed by Istituto Italiano di Tecnologia, with headquarters in Genoa, Via Morego 30, acting as the Data Holder, using computer and paper based means, observing the rules on protection of personal data, including those relating to the security of data. Please also note that, pursuant to art.7 of Legislative Decree 196/2003, you may exercise your rights at any time as a party concerned by contacting the Data Manager. Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce. From zk240 at cam.ac.uk Fri Nov 17 04:52:08 2017 From: zk240 at cam.ac.uk (Zoe Kourtzi) Date: Fri, 17 Nov 2017 09:52:08 +0000 Subject: Connectionists: PhD studentship in Machine Learning and NeuroImaging In-Reply-To: References: Message-ID: <6168FCB8-2A43-46B6-81D5-1C18810DCF31@cam.ac.uk> Applications are invited for a 4-year BBSRC Targeted PhD studentship in the area of Machine Learning and NeuroImaging starting in October 2018 at the Adaptive Brain Lab (http://www.abg.psychol.cam.ac.uk ) Department of Psychology, University of Cambridge. The project focuses on machine learning applications in cognitive neuroscience. We aim to develop predictive models that synthesise multivariate data to define profiles of individual neuro-cognitive health. We address this challenge using an interdisciplinary approach that combines state-of-the-art mathematical modelling with behavioural paradigms, and brain imaging. Our team works with computer scientists, mathematicians, cognitive neuroscientists and industrial partners to translate our research to user-friendly tools that can be used to assess and promote cognitive health across the lifespan. For further details and to apply for the post please check: http://www.jobs.cam.ac.uk/job/15753/ Please note closing date for applications is Dec 6th, 2017 For informal inquiries please contact Prof Zoe Kourtzi >. Please include a CV and statement of research background and interests -------------- next part -------------- An HTML attachment was scrubbed... URL: From antonino.staiano at uniparthenope.it Fri Nov 17 12:10:31 2017 From: antonino.staiano at uniparthenope.it (Antonino Staiano) Date: Fri, 17 Nov 2017 18:10:31 +0100 Subject: Connectionists: Call for Papers of VSI on: MACHINE LEARNING AND BIO-INSPIRED COMPUTATION AID TO INFORM COMPLEX ENVIRONMENTAL DECISIONS Message-ID: Call for Papers of Virtual Special Issue on: MACHINE LEARNING AND BIO-INSPIRED COMPUTATION AID TO INFORM COMPLEX ENVIRONMENTAL DECISIONS The call is available at *https://www.journals.elsevier.com/ecological-informatics/call-for-papers/call-for-papers-of-virtual-special-issue-on-machine-learning * *Guest Editors*: Antonino Staiano (a)?Friedrich Recknagel (b) (a). Department of Science and Technology, University of Naples Parthenope, Italy (b). School of Biological Sciences, University of Adelaide, Australia Scope: Environmental decision makers and scientists face highly dynamic and complex problems that require suitable quantitative tools for data analysis, synthesis and forecasting. To name just a few examples, forecasting of the export of nutrients from river basins, salinity, ozone levels, air pollution, algal growth and transport in lakes and rivers, or assessing risks of species extinction by bioinvasion and degradation of pesticides in soils, often exceed potential of statistical analysis and simple mathematical modeling. Machine learning techniques such as artificial neural networks, evolutionary algorithms, regression trees, fuzzy and neuro-fuzzy modeling as well as bio-inspired computation such as immuno-computing, prove to be very efficient in coping with highly complex and non-linear problems. The aim of the proposed special issue is to draw special attention to current applications and future potential of machine learning and bio-inspired computation in the field of environmental analysis and management, and to stimulate interdisciplinary collaborations in this challenging research field. Researchers and practitioners in computer science, artificial intelligence, natural and environmental sciences are invited to submit papers on applications of machine learning and bio-inspired computation to problems like impacts of pollution, global warming, habitat degradation and bioinvasion on terrestrial and aquatic populations, communities and ecosystems, pesticide risk assessment. If you are interested in submitting a paper to the VSI, please submit your manuscript to the EVISE system https://www.evise.com/profile/api/navigate/ECOINF. Authors must select ?VSI:AI-aided decision making? in the submission process. Timeline: May 15 2018: submission deadline August 2018: first round review September 2018: final submission November 2018: publication Contact information: antonino.staiano at uniparthenope.it Antonino Staiano, PhD Assistant Professor Dept. Science and Technology University of Naples Parthenope, Italy -------------- next part -------------- An HTML attachment was scrubbed... URL: From sroy at biostat.wisc.edu Fri Nov 17 17:26:12 2017 From: sroy at biostat.wisc.edu (Sushmita Roy) Date: Fri, 17 Nov 2017 16:26:12 -0600 Subject: Connectionists: Assistant/Associate/Full Professor positions in Machine learning/Data science at UW Madison Message-ID: <2ccf67fb-f9e9-5771-04f5-1d3fab11d15c@biostat.wisc.edu> The Department of Biostatistics & Medical Informatics (BMI) at the University of Wisconsin School of Medicine & Public Health (SMPH) seeks tenure track assistant, associate, and full professors whose research focuses on machine learning, or related areas, to start in Fall 2018. Candidates should have a doctoral degree (PhD, ScD, or equivalent) in Computer Science, Biomedical Informatics, Bioinformatics, Computational Biology, or a closely related quantitative area. We are particularly interested in machine learning or data science experts with experience or a demonstrated interest in motivating their methodological research by any of the vast array of applications in the biological, clinical, or public health sciences. Other relevant methodological expertise may include, but is not limited to, database theory and methods and/or data mining, natural language processing, and data privacy and security. A key consideration is the ability and interest to work in a collaborative, interdisciplinary environment. A review of complete applications will begin on December 15, 2017. To ensure full consideration, please apply by January 1, 2018. The position will remain open and applicants may be considered until the position is filled. Candidates should submit their applications through the UW employment PVL (link is external). Full position description: https://biostat.wisc.edu/sites/default/files/Faculty%20Ad%20-%20Medical%20Informatics-Fall2017-Final.pdf Official position listing: http://jobs.hr.wisc.edu/cw/en-us/job/496600/professor (link is external) Application Deadline: Monday, January 1, 2018 -- Sushmita Roy Assistant Professor Biostatistics and Medical Informatics Wisconsin Institute for Discovery University of Wisconsin, Madison pages.discovery.wisc.edu/~sroy From ksmith at kth.se Fri Nov 17 14:53:09 2017 From: ksmith at kth.se (Kevin Smith) Date: Fri, 17 Nov 2017 20:53:09 +0100 Subject: Connectionists: [Job] Postdoc in deep learning for medical image analysis, KTH Royal Institute of Technology, Stockholm Message-ID: Job description This position is part of a collaboration with physicians from the Karolinska University Hospital. The main task will be to develop deep learning methods to analyse medical images, focusing on breast cancer. The successful applicant will apply his/her knowledge in deep learning to several types of medical images, including histological sections, mammograms, and possibly others. Generally, the goal will be towards predicting patient outcome, but we aim to develop models for specific predictors of patient outcome, such as tumour heterogeneity biomarkers and risk models. In additional to these medical applications, the successful candidate will also participate in theoretical research in deep learning and computer vision. Other duties include helping to mentor MSc and PhD students, and potential teaching duties. The position is initially funded for one year, with a possibility for extension contingent upon funding and eligibility. Qualifications Candidates must have a PhD in computer science, computational science, or a related field received within the last three years. Proven knowledge and ability in one or more deep learning frameworks (Tensorflow, Keras, Torch, Caffe, etc) is absolutely required. Also required is knowledge of standard computer vision techniques and experience in implementing, analysing, and optimizing scientific applications for image analysis. Proficiency in one or two scientific computing languages (Python, Matlab, R) is required. Experience with parallel programming environments and cloud computing is a plus. Previous experience working with medical or biological images is also desirable. *KTH Royal Institute of Technology* KTH Royal Institute of Technology in Stockholm has grown to become one of Europe?s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden?s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as in architecture, industrial management, urban planning, history and philosophy. For information about the School of Computer Science and Communication, please visit https://www.kth.se/en/csc. Department information The position will be formally placed with the department for Computational Science and Technology (CST) at KTH, but work will be carried out at the Science for Life Laboratory. The CST department conducts research to understand and model physical and biological systems using computational techniques, which require efficient, high performance algorithms and implementations together with advanced visual analysis capabilities. For more information go to https://www.kth.se/en/csc/forskning/cst. The Science for Life Laboratory (SciLifeLab) is a collaboration between four universities in Stockholm and Uppsala: Karolinska Institutet, KTH, Stockholm University and Uppsala University. It combines advanced technology with broad knowledge in translational medicine and molecular life sciences. Since 2013, SciLifeLab has a mission from the Swedish government to run infrastructure to support researchers nationally and to be an internationally leading center for large-scale analyses in molecular life sciences targeting research in health and environment. For more information, visit https://www.scilifelab.se/. Trade union representatives You will find contact information to trade union representatives at KTH:s webbpage . Application Log into KTH's recruitment system in order to apply to this position. You are the main responsible to ensure that your application is complete according to the ad. Your complete application must be received at KTH no later than the last day of application, midnight CET/CEST (Central European Time/Central European Summer Time). Applications shall include the following documents: 1. Statement of interest including a brief description of experience in deep learning 2. Curriculum vitae 3. Transcripts from university 4. Reference contact information 5. Representative publications (or other example of scientific writing) Please observe that all material needs to be in English. Others We firmly decline all contact with staffing and recruitment agencies and job ad salespersons. Disclaimer: In case of discrepancy between the Swedish original and the English translation of the job announcement, the Swedish version takes precedence. Type of employment Temporary position longer than 6 months Contract type Full time First day of employment According to the agreement Salary Monthly salary Number of positions 1 Working hours 100% City Solna County Stockholms l?n Country Sweden Reference number D-2017-0814 Contact - Kevin Smith / Bitr universitetslektor, ksmith at kth.se, +46 8 790 64 37 - Maria Engman / HR-administrat?r, maengm at kth.se Published 14.Nov.2017 Last application date 06.Jan.2018 11:59 PM CET -------------- next part -------------- An HTML attachment was scrubbed... URL: From fasoto at fiu.edu Fri Nov 17 17:06:06 2017 From: fasoto at fiu.edu (=?UTF-8?B?RmFiacOhbiBTb3Rv?=) Date: Fri, 17 Nov 2017 17:06:06 -0500 Subject: Connectionists: Cognitive Neuroscience Tenure Track Position, FIU in Miami Message-ID: The Department of Psychology at Florida International University (FIU) is searching for an open-rank tenure track position in Cognitive Neuroscience. Candidates in all areas of Cognitive Neuroscience will be considered, including human or animal (avian or rodent) neuroscience. Expertise using cutting-edge methodologies for research in Cognitive Neuroscience and Neuropsychology is expected (e.g., magnetic resonance imaging, near-infrared spectroscopy, electroencephalography, transcranial magnetic stimulation, confocal microscopy). The ideal candidate would complement the existing faculty in Cognitive Neuroscience, Legal Psychology, Clinical Science, Developmental Science, or Industrial/Organizational doctoral programs. Mid-rank and senior candidates must have a strong record of publications and substantial active federal grant funding. Junior candidates must have a demonstrated evidence of or very strong potential for extramural funding and a solid record of scholarship in refereed journals. Currently, department faculty hold over $45 million in grants from federal agencies (e.g., NIMH, NICHD, NIDA, NIAAA, IES, NSF, DoJ) and the department ranks 44th nationally on research and development expenditures according to the NSF Higher Education Research and Development Survey. Collaborative research is emphasized and many faculty share investigator status on grants. The department is closely affiliated with the Center for Children and Families (CCF) and the Center for Imaging Science (CIS). The CIS includes a research-dedicated magnetic resonance imaging (MRI) facility that supports a 3T Siemens MAGNETOM Prism and is equipped to run the Human Connectome Protocol. The department also has access to state-of-the-art animal care facilities for rodent, avian, and large animal research, as well as wet-lab and optical imaging equipment supporting researchers in behavioral neuroscience. For more information, go to https://facultycareers.fiu.edu/?posting=514307 -- Fabian A. Soto Assistant Professor Department of Psychology Florida International University Modesto A. Maidique Campus 11200 SW 8th St, AHC4 460 Miami, FL 33199 Phone: 305-348-8423 <%28305%29%20348-8423> Fax: 305-348-6670 <%28305%29%20348-6670> Email: fabian.soto at fiu.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From mccallum at cs.umass.edu Sun Nov 19 14:43:40 2017 From: mccallum at cs.umass.edu (Andrew McCallum) Date: Sun, 19 Nov 2017 14:43:40 -0500 Subject: Connectionists: Faculty positions at UMass Amherst: junior & senior openings in data science Message-ID: UMass Amherst Computer Science is hiring faculty in data science broadly this year and for multiple years to come---at both the junior and senior levels. Review of applications this season is continuing according to the typical CS timing: peaking in December and early January, with interviews starting in late January or early February 2018. We have 5 openings in data science this year; 10+ openings over the coming several years; (there are additional faculty openings in other areas this year, as well, including a separate search in data science theory). I am chairing data science faculty recruiting. I would be happy to receive email and answer questions. https://www.cics.umass.edu/job/assistantassociate-professor-positions-data-science Please forward this message to anyone who might be interested. Best, Andrew McCallum Professor; Director, Center for Data Science College of Information and Computer Sciences UMass Amherst =============================================================== data science, broadly: machine learning & decision-making, broadly systems & scalable data management, broadly theory & algorithms for big data, broadly ...non-exclusive list of examples: Methods: algorithms for big data artificial intelligence & ML with big data databases decision processes and reinforcement learning deep learning distributed systems game theory, mechanism design learning theory optimization parallel-distributed machine learning probabilistic programming scalable probabilistic inference statistical machine learning visualization, interpretable ML, and data exploration Modalities: crowd sourcing and human computation images & video information integration natural language processing sensor networks and wearable sensors social networks and computational social science Applications: agriculture, climate, ecology and sustainability computational economics computational biology & bio-medicine education eGovernment energy eScience finance health analytics internet of things manufacturing cities & regions =============================================================== Our Department became a College in 2015 and we are dramatically growing our current set of ~50 faculty. UMass CS is highly ranked in AI, exceptionally collaborative, and has long-standing broad interests touching many areas of data science. Selected current faculty include: * Mohit Iyyer (NLP & deep learning) * Marco Serafini (distributed systems, databases) * Rahman Tauhidur (mobile health, embedded systems, ML) * Laura Haas (information integration, databases) * Peter Haas (information management) * Justin Domke (ML & optimization) * Sunghoon Ivan Lee (mobile & personalized health) * Phillipa Gill (networking & security) * Akshay Krishnamurthy (statistical machine learning) * Arya Mazumdar (information theory) * Joydeep Biswas (robotics) * Subhransu Maji (computer vision & ML) * Brendan O'Connor (NLP and computational social science) * Barna Saha (algorithms & data management) * Alexandra Meliou (databases, analytics & causality, fairness) * Yuriy Brun (software engineering, analytics, fairness) * Dan Sheldon (computational ecology & ML) * Evangelos Kalogerakis (graphics & ML) * Ben Marlin (ML, health analytics) * Deepak Ganesan (sensor and mobile networks, wearable health) * Yanlei Diao (databases) * Gerome Miklau (databases & privacy) * Andrew McGregor (algorithms) * Rui Wang (graphics) * Erik Learned-Miller (computer vision & ML) * David Jensen (data mining & causality) * Andrew McCallum (information extraction & ML) * Brian Levine (security) * Prashant Shenoy (distributed systems, cloud computing) * Ramesh Sitaraman (theory & parallel/distributed systems) * Shlomo Zilberstein (AI) * James Allan (information retrieval) * Beverly Woolf (intelligent tutoring systems) * Rod Grupen (robotics) * Jim Kurose (networking, on leave as head of NSF CISE) * Neil Immerman (complexity theory) * Bruce Croft (information retrieval) * Don Towsley (networking) =============================================================== ASSISTANT/ASSOCIATE PROFESSOR POSITIONS-DATA SCIENCE About University of Massachusetts Amherst: Our college is highly supportive of junior faculty, providing both formal and informal mentoring. Many of our faculty are involved in interdisciplinary research, working closely with other departments including statistics/mathematics, linguistics, electrical and industrial engineering, biology, physics, behavioral sciences, economics, political science, and nursing, as well as new green initiatives. Amherst, a historic New England town, is the center of a vibrant and culturally rich area that includes five colleges. For more information about our college, visit https://cics.umass.edu . Job Description: The College of Information and Computer Sciences at the University of Massachusetts Amherst invites applications for multiple tenure-track faculty positions in Computer Science for the 2018-2019 academic year. Multiple openings are available for Assistant and Associate level Professors in the field of Data Science. Under exceptional circumstances, highly qualified candidates at other ranks may receive consideration for these openings. Requirements: Applicants must have a Ph.D. in Computer Science or a related area, and should show evidence of exceptional research promise. Additional Information: Rank and salary will be highly competitive and commensurate with qualifications and experience. Inquiries and requests for more information can be sent to: facrec at cs.umass.edu . The university is committed to active recruitment of a diverse faculty and student body. The University of Massachusetts Amherst is an Affirmative Action/Equal Opportunity Employer of women, minorities, protected veterans, and individuals with disabilities and encourages applications from these and other protected group members. Because broad diversity is essential to an inclusive climate and critical to the University's goals of achieving excellence in all areas, we will holistically assess the many qualifications of each applicant and favorably consider an individual's record working with students and colleagues with broadly diverse perspectives, experiences, and backgrounds in educational, research or other work activities. We will also favorably consider experience overcoming or helping others overcome barriers to an academic degree and career. Application Instructions: All applicants should submit a cover letter, curriculum vitae, research statement, and statement of teaching interests via the UMass website. Applicants at the Assistant Professor level should submit the names and contact information for three references and links to two papers that best represent their research/experience. Applicants at the Associate Professor level should submit the names and contact information for four references and links to three papers that best represent their research/experience. Review of applications will begin on September 28, 2017 for consideration during the fall 2017/winter 2018 hiring period. -------------- next part -------------- An HTML attachment was scrubbed... URL: From juergen at idsia.ch Mon Nov 20 09:52:42 2017 From: juergen at idsia.ch (Juergen Schmidhuber) Date: Mon, 20 Nov 2017 15:52:42 +0100 Subject: Connectionists: [jobs] PostDocs & PhD Students at the Swiss AI Lab, IDSIA Message-ID: <9667B353-CDB2-44BF-9CEF-ADB78ACAABA4@idsia.ch> We intend to interview prospective PhD students and postdocs on Dec 2-11 at NIPS 2017 in Long Beach, CA. Please find application instructions under http://people.idsia.ch/~juergen/erc2017.html J?rgen Schmidhuber Scientific Director, Swiss AI Lab, IDSIA Professor of AI, USI & SUPSI, Switzerland Chief Scientist, NNAISENSE http://people.idsia.ch/~juergen/whatsnew.html . From J.Bowers at bristol.ac.uk Mon Nov 20 12:36:52 2017 From: J.Bowers at bristol.ac.uk (Jeffrey Bowers) Date: Mon, 20 Nov 2017 17:36:52 +0000 Subject: Connectionists: Postdoctoral positions and PhD Studentships Message-ID: Postdoctoral positions and PhD Studentships for ERC Advanced Grant entitled: ?Generalization in Mind and Machine?. Based at the University of Bristol, UK. Please go to the following link to find out more about this project: https://jeffbowers.blogs.ilrt.org/researchgrants/ If you are potentially interested in a position please send me your CV and a short statement explaining why you are interested. I will be at NIPS 2017 and if I think there might be a fit I would be happy to meet up and talk more about the project. I anticipate officially advertising for posts early in the new year. Unlike most work with deep neural network, this project uses networks with the intention to better understand the human mind/brain. For one post I would like to hire a computer scientist with expertise in deep learning. In this case, knowledge of psychology and neuroscience desirable, but not strictly necessary. For other posts, modelling in psychology and neuroscience is a prerequisite. For PhD positions a modelling background is desirable, but not strictly necessary. To have a better idea of the perspective I take on neural network modelling, please see the following paper: https://jeffbowers.blogs.ilrt.org/files/2017/11/bowers-tics-2017.pdf Feel free to contact me if you have any questions. Sincerely, Jeff Bowers j.bowers at bristol.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: From mpavone at dmi.unict.it Tue Nov 21 05:05:33 2017 From: mpavone at dmi.unict.it (Mario Pavone) Date: Tue, 21 Nov 2017 11:05:33 +0100 Subject: Connectionists: 1st CfP: international Metaheuristics Summer School - MESS 2018 Message-ID: <20171121110533.Horde.SxEBd_ph4B9aE-ptx0D0ERA@mbox.dmi.unict.it> 1st Call for Participation (apologies for multiple copies) ----------------------------------------------------------------------- MESS 2018 - Metaheuristics Summer School - from Design to Implementation - 21-25 July 2018, Taormina, Italy https://www.ANTs-lab.it/mess2018/ mess.school at ANTs-lab.it ----------------------------------------------------------------------- ** APPLICATION DEADLINE: 15th April 2018 ** MESS 2018 is aimed at qualified and strongly motivated MSc and PhD students; post-docs; young researchers, and both academic and industrial professionals to provide an overview on the several metaheuristics techniques, and an in-depth analysis of the state-of-the-art. As first edition, MESS 2018 wants to analyze all metaheuristics from its designing to its implementation. In particular, in MESS 2018 will be analyzed modern heuristic methods for search and optimization problems, as well as the classical exact optimization methods, seen also in the metaheuristics context. All participants will have plenty of opportunities for debate and work with leaders in the field, benefiting from direct interaction and discussions in a stimulating environment. They will also have the possibility to present their recently results and/or their working in progress through oral or poster presentations, and interact with their scientific peers, in a friendly and constructive environment. ** Confirmed Speakers + Christian Blum, IIIA-CSIC, Barcelona, Spain + Salvatore Greco, University of Catania, Italy & University of Portsmouth, UK + Gunther Raidl, Technische Universitat Wien, Austria + Celso Ribeiro, Universidade Federal Fluminense, Brazil + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy More Speakers will be announced soon!! ** Short Talk and Poster Presentation All participants may submit an abstract of their recent results, or works in progress, for presentation and having the opportunities for debate and interact with leaders in the field. Mini-Workshop Organizers and Scientific Committee will review the abstracts and will recommend for the format of the presentation (oral or poster). All abstracts will be published on the electronic hands-out book of the summer school. The Abstracts must be submitted by *April 15, 2018*. ** School Directors + Salvatore Greco, University of Catania, Italy + Panos Pardalos, University of Florida, USA + Mario Pavone, University of Catania, Italy + El-Ghazali Talbi, University of Lille 1, France + Daniele Vigo, University of Bologna, Italy ** Oral & Poster Presentation Organizers + Luca Di Gaspero, Unviersity of Udine, Italy + Paola Festa, University of Naples "Federico II", Italy https://www.ANTs-lab.it/mess2018/ -- mess.school at ANTs-lab.it Facebook Group: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school -- Dr. Mario Pavone (PhD) Assistant Professor Department of Mathematics and Computer Science University of Catania V.le A. Doria 6 - 95125 Catania, Italy tel: 0039 095 7383034 fax: 0039 095 330094 Email: mpavone at dmi.unict.it http://www.dmi.unict.it/mpavone/ =========================================================== MESS 2018 - Metaheuristics Summer School 21-25 July 2018, Taormina, Italy W: https://www.ANTs-lab.it/mess2018/ E: mess.school at ANTs-lab.it FB: https://www.facebook.com/groups/MetaheuristicsSchool/ Twitter: https://twitter.com/MESS_school =========================================================== From M.Gillies at gold.ac.uk Tue Nov 21 06:59:47 2017 From: M.Gillies at gold.ac.uk (Marco Gillies) Date: Tue, 21 Nov 2017 11:59:47 +0000 Subject: Connectionists: Fwd: Fully Funded IGGI PhD Studentships In-Reply-To: References: Message-ID: ________________________________ From: Jeremy Gow Sent: Monday, November 20, 2017 11:30:04 AM To: all at doc.gold.ac.uk Subject: Fully Funded IGGI PhD Studentships EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (IGGI) 12 fully-funded PhD studentships to start September 2018 Covers fees at Home/EU rate and a stipend for four years http://iggi.org.uk/apply IGGI is an exciting opportunity for you to undertake a four-year PhD in Intelligent Games and Game Intelligence, working with top games companies and world-leading academics in games research. We currently have 46 students conducting interdisciplinary research in areas such as: * AI (Artificial Intelligence) to create interesting, fun, believable game agents, * AI-assisted game design and testing, * procedural content generation, * emotion and immersion in games, * interaction design for games, * Machine Learning (ML) to understand player psychology * using games for learning and wellbeing, * game audio, graphics and animation * game design, citizen science and gamification. IGGI is a collaboration between the University of York, the University of London (Goldsmiths and Queen Mary) and the University of Essex. The programme trains PhD researchers who will become the next generation of leaders in research, design, development and entrepreneurship in digital games. We have 12 studentships available for 2018/19 entry, which will fund full fees (at a Home/ EU rate) plus a tax-free living stipend, for a 4-year PhD programme. Could you join our large and growing group of games researchers in the world?s largest games research programme? Why IGGI? IGGI gives you the opportunity to work with our industry partners, allowing you the possibility to contribute directly to the future of games. You will have the opportunity to undertake industrial placements during the IGGI programme, giving you first-hand experience of the games industry. These placements will contribute to your research, ensuring its relevance, as well as giving you the skills needed to succeed in a career in the games industry or games research. Our students have completed, or are currently on, placements with partner companies such as Sony Interactive Entertainment, Bossa Studios, Google, Bloomberg, PROWLER.io, Media Molecule, BT, Splash Damage, and MindArk. Other partners include organisations such as Electronic Arts, Creative Assembly, Rebellion, Revolution, AI Factory and over 50 games companies and organisations which use games in creative ways (see http://www.iggi.org.uk/industry-partners/) Your research work with partners like these will advance the creation of more fun and profitable games that exploit research advances, and help to increase the use of games as tools for research in behavioural science and for societal benefit. You?ll also learn through teamwork and inspiring events such as: * the IGGI Game Jam, a 48 hour game development challenge as part of the Global Game Jam, enhancing your skills in game design, development, and teamwork; * the IGGI Conference, showcasing student research alongside industry and academic speakers; * student-led events such as the IGGI Game Creator?s Club, research seminars, games evenings. You?ll receive focused skills training from a range of academic research leaders, covering topics including Games Development, Games Design and Research Skills as well as a range of optional topics in areas such as AI, HCI, graphics, audio and design. Apply for IGGI We have 12 fully-funded studentships to award to outstanding students which cover fees and an annual tax-free stipend of ?14,553 (or ?16,000 with London weighting if studying at Goldsmiths or Queen Mary) for four years (at 2017/18 rates - this is likely to increase slightly for September 2018 starters). An IGGI application should consist of a CV, a covering letter explaining your motivation and suitability for the IGGI programme, and a statement of your planned research and proposed supervisor(s). You will also be asked for evidence of your programming skills during the application process, either through your qualifications, previous employment or examples of games you have developed. You can contact potential supervisors directly (see http://www.iggi.org.uk/supervisors/ for a list), or contact us at the email address below and we can help you to choose a principal supervisor from York, Essex, Goldsmiths, or Queen Mary based on your interests and background. We expect substantial competition for IGGI studentships and we encourage good students to submit applications as early as possible. The deadline for applications is 23:59 (GMT) on Wednesday 31st January 2018. Interviews will take place at University of York on Friday 16th March 2018. Please email your CV, covering letter, supervisor information and statement of planned research to apply at iggi.org.uk. Enquiries should be sent to the same email address. IGGI students are a diverse group, and admission judgements are made exclusively on the basis of experience and potential to do excellent research and contribute to IGGI?s goals. We especially welcome applications from female and minority ethnic candidates as well as other groups that are under-represented in areas related to IGGI. -------------- next part -------------- An HTML attachment was scrubbed... URL: From k.wong-lin at ulster.ac.uk Tue Nov 21 07:31:22 2017 From: k.wong-lin at ulster.ac.uk (Wong-Lin, Kongfatt) Date: Tue, 21 Nov 2017 12:31:22 +0000 Subject: Connectionists: Multiple academic positions in Cognitive Analytics Research Laboratory, Ulster University Message-ID: Several academic positions in data analytics, including neuroinformatics, are available at Ulster University. They range from Lecturership (Assistant Professorship equivalent) to (Full) Professorship. The application deadline is 8 December 2017. Best, KongFatt Wong-Lin https://www.ulster.ac.uk/staff/k-wong-lin ----------------------------------------------------------------------- Professor of Data Analytics (2 posts) http://www.jobs.ac.uk/job/BFM233/professor-of-data-analytics-2-posts/ Readers/Senior Lecturers in Data Analytics (3 posts) http://www.jobs.ac.uk/job/BFM247/reader-senior-lecturer-in-data-analytics-3-posts/ Lecturers in Data Analytics (3 posts) http://www.jobs.ac.uk/job/BFM258/lecturer-in-data-analytics/ Ulster University ? Cognitive Analytics Research Laboratory, Faculty of Computing, Engineering and the Built Environment An exciting opportunity to contribute to internationally recognised research and help shape the future of data analytics. Ulster is a university in the top 3% globally, where excellence in teaching is underpinned by world-leading research. Ranked as one of the world?s top 150 young universities and in the top 25% of UK universities for overall research, Ulster is ambitious, forward-thinking and outward-looking. Our new Cognitive Analytics Research Laboratory is Northern Ireland?s first data analytics institute. It is a ?4 million investment that brings together businesses, government and advanced academic research expertise to find innovative application areas for cognitive analytics techniques. It is part of an exciting programme of investment in new infrastructure and initiatives driven by a five-year strategic vision to deliver a university that is sustainable and innovative with a strong international reputation. Ulster has a long history of expertise in data analytics in both machine learning algorithms and the application of analytical techniques across a diverse range of domains including Health and Neuroinformatics. We are seeking to appoint talented and creative people with a genuine passion for their work, who will deliver outstanding research and teaching that encourages innovation, leadership and vision. The appointment is permanent and is open to applications from individuals or teams. Location: Magee campus, Derry~Londonderry. Attractive reward package including a competitive starting salary, pension scheme and financial assistance with relocation. Closing date for applications: 8 December 2017. For more information about this opportunity visit: www.ulster.ac.uk/jobs ------------------------------------------------ This email and any attachments are confidential and intended solely for the use of the addressee and may contain information which is covered by legal, professional or other privilege. If you have received this email in error please notify the system manager at postmaster at ulster.ac.uk and delete this email immediately. Any views or opinions expressed are solely those of the author and do not necessarily represent those of Ulster University. The University's computer systems may be monitored and communications carried out on them may be recorded to secure the effective operation of the system and for other lawful purposes. Ulster University does not guarantee that this email or any attachments are free from viruses or 100% secure. Unless expressly stated in the body of a separate attachment, the text of email is not intended to form a binding contract. Correspondence to and from the University may be subject to requests for disclosure by 3rd parties under relevant legislation. The Ulster University was founded by Royal Charter in 1984 and is registered with company number RC000726 and VAT registered number GB672390524.The primary contact address for Ulster University in Northern Ireland is Cromore Road, Coleraine, Co. Londonderry BT52 1SA -------------- next part -------------- An HTML attachment was scrubbed... URL: From sahidullahmd at gmail.com Tue Nov 21 08:14:59 2017 From: sahidullahmd at gmail.com (Md Sahidullah) Date: Tue, 21 Nov 2017 18:44:59 +0530 Subject: Connectionists: Three Postdoctoral Researchers/Project Researchers (Speech Processing and Deep Learning) Message-ID: Three Postdoctoral Researchers/Project Researchers (Speech processing and deep learning) The University of Eastern Finland, UEF, is one of the largest multidisciplinary universities in Finland. We offer education in nearly one hundred major subjects, and are home to approximately 15,000 students and 2,500 members of staff. From 1 August 2018 onwards, we?ll be operating on two campuses, in Joensuu and Kuopio. In international rankings, we are ranked among the leading universities in the world. The Faculty of Science and Forestry operates on the Kuopio and Joensuu campuses of the University of Eastern Finland. The mission of the faculty is to carry out internationally recognised scientific research and to offer research-education in the fields of natural sciences and forest sciences. The faculty invests in all of the strategic research areas of the university. The faculty?s environments for research and learning are international, modern and multidisciplinary. The faculty has approximately 3,800 Bachelor?s and Master?s degree students and some 490 postgraduate students. The number of staff amounts to 560. http://www.uef.fi/en/lumet/etu sivu We are now inviting applications for three Postdoctoral Researcher/Project Researcher positions in speech processing and deep learning funded by Academy of Finland, School of Computing, Joensuu Campus. o Two positions in automatic speaker rec, voice conversion, anti-spoofing (NOTCH project) o One position in deep reinforcement learning for physical agents (DEEPEN project) The two projects share similarities in terms of machine learning methods being used and developed further, but are otherwise differently focused. The NOTCH research project (NOn-cooperaTive speaker CHaracterization), being led by Associate Professor Tomi Kinnunen, aims at advancing state-of-the-art in automatic speaker verification (defense) and voice conversion (attack) under a generic umbrella of non-cooperative speech, whether being induced by spoofing attacks, disguise, or other intentional voice modifications. A successful applicant needs to have background in speaker verification, anti spoofing, voice conversion, machine learning or closely related topics. The DEEPEN research project (Deep Reinforcement Learning for Physical Agents) is run in co operation between UEF and robotics group at Aalto University. UEF?s part, lead by Senior Researcher Ville Hautam?ki, aims at designing new statistical models for simulated robot control and to take steps towards solving the so-called ?reality gap? problem. The post-doc may also contribute to speech and deep learning topics. A successful applicant needs to have background in deep learning, reinforcement learning, speech technology or machine vision. Practical experience in DRL research environments (e.g. VizDoom or MuJoCo), will be counted as a plus. The Machine Learning group of the School of Computing, at the facilities of Joensuu Science Park, provides access to modern research infrastructure and is a strongly international working environment. We hosted the Odyssey 2014 conference, were a partner in the H2020-funded OCTAVE project, and are a co-founder of the Automatic Speaker Verification and Countermeasures (ASVspoof) challenge series (http://www.asvspoof.org/). A person to be appointed as a postdoctoral researcher shall hold a suitable doctoral degree that has been awarded less than five years ago. If the doctoral degree has been awarded more than five years ago, the post will be one of a project researcher. The doctoral degree should be in spoken language technology, electrical engineering, computer science, machine learning or a closely related field. Researchers finishing their PhD in the near future are also encouraged to apply for the positions. However, they are expected to hold a PhD degree by the starting date of the position. We expect strong hands-on experience and creative out-of-the-box problem solving attitude. A successful applicant needs to have an internationally proven track record in topics relevant to the project he or she applies to. English may be used as the language of instruction and supervision in these positions. The positions will be filled from earliest January 1, 2018 for a period of 12 months. The continuation of the position will be agreed separately. The position will be filled for a fixed term due to pertaining to a specific project (Postdoctoral researcher positions shall always be filled for a fixed term, UEF University Regulations 31 ?). The salary of the position is determined in accordance with the salary system of Finnish universities and is based on level 5 of the job requirement level chart for teaching and research staff (?2.865,30/ month). In addition to the job requirement component, the salary includes a personal performance component, which may be a maximum of 46.3% of the job requirement component. For further information on the position, please contact (NOTCH): Associate Professor Tomi Kinnunen, email: tkinnu at cs.uef.fi, tel. +358 50 442 2647 <+358%2050%204422647> and (DEEPEN): Senior Researcher Ville Hautam?ki, email: villeh at cs.uef.fi, tel. +358 50 511 8271 <+358%2050%205118271>. For further information on the application procedure, please contact: Executive Head of Administration Arja Hirvonen, tel. +358 44 716 3422 <+358%2044%207163422>, email: arja.hirvonen at uef.fi. A probationary period is applied to all new members of the staff. You can use the same electronic form to apply for both research projects. The electronic application should contain the following appendices: - a r?sum? or CV - a list of publications - copies of the applicant's academic degree certificates/ diplomas, and copies of certificates / diplomas relating to the applicant?s language proficiency, if not indicated in the academic degree certificates/diplomas - motivation letter - a cover letter indicating the position to be applied for - The names and contact information of at least two referees are requested in the application form. The application needs to be submitted no later than December 22, 2017 (by 24:00 EET) by using the electronic application form. Navigate to http://www.uef.fi/en/uef/en-open-positionsand search for ?Three Postdoctoral Researchers/Project Researchers (Speech processing and deep learning)? to find the link to the electronic application form. -- Dr. Md Sahidullah tel. +358-466250731 or +91-9433289799 website: *https://sites.google.com/site/iitkgpsahi/ * -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: NOTCH-DEEPEN-announcement-final.pdf Type: application/pdf Size: 221176 bytes Desc: not available URL: From hava.siegelmann at gmail.com Tue Nov 21 13:24:46 2017 From: hava.siegelmann at gmail.com (Hava Siegelmann) Date: Tue, 21 Nov 2017 13:24:46 -0500 Subject: Connectionists: DARPA small grants are available Message-ID: https://spectrum.ieee.org/cars-that-think/robotics/artificial-intelligence/darpa-seeking-ai-that-can-learn-all-the-time -------------- next part -------------- An HTML attachment was scrubbed... URL: From erishabh at gmail.com Tue Nov 21 12:17:04 2017 From: erishabh at gmail.com (Rishabh Mehrotra) Date: Tue, 21 Nov 2017 17:17:04 +0000 Subject: Connectionists: WSDM Workshop on Learning from User Interactions (Deadline 30th Nov) Message-ID: *WSDM Workshop on Learning from User Interactions* We invite contributions to WSDM Workshop on Learning from User Interactions at WSDM 2018 to be held in Los Angeles, 6 - 8 Feb 2018. *TL;DR**:* 4-6 pages, in WSDM format, submit by November 30th. Workshop Website: https://task-ir.github.io/wsdm2018-learnIR-workshop/ Submission Link: Easychair Twitter: https://twitter.com/learnIRWSDM We intend to have a sponsored Best Paper award alongside potential registration support for students. *Overview* While users interact with online services (e.g. search engines, recommender systems, conversational agents), they leave behind fine grained traces of interaction patterns. The ability to understand user behavior, record and interpret user interaction signals, gauge user satisfaction and incorporate user feedback gives online systems a vast treasure trove of insights for improvement and experimentation. More generally, the ability to learn from user interactions promises pathways for solving a number of problems and improving user engagement and satisfaction. Understanding and learning from user interactions involves a number of different aspects - from understanding user intent and tasks, to developing user models and personalization services. A user's understanding of their need and the overall task develop as they interact with the system. Supporting the various stages of the task involves many aspects of the system, e.g. interface features, presentation of information, retrieving and ranking. Often, online systems are not specifically designed to support users in successfully accomplishing the tasks which motivated them to interact with the system in the first place. Beyond understanding user needs, learning from user interactions involves developing the right metrics and expiermentation systems, understanding user interaction processes, their usage context and designing interfaces capable of helping users. Learning from user interactions becomes more important as new and novel ways of user interactions surface. There is a gradual shift towards searching and presenting the information in a conversational form. Chatbots, personal assistants in our phones and eyes-free devices are being used increasingly more for different purposes, including information retrieval and exploration. With improved speech recognition and information retrieval systems, more and more users are increasingly relying on such digital assistants to fulfill their information needs and complete their tasks. Such systems rely heavily on quickly learnig from past interactions and incorporating implicit feedback signals into their models for rapid development. Topics Learning from User Interactions will be a highly interactive full day workshop that will provide a forum for academic and industrial researchers working at the intersection of user understanding, search tasks, conversational IR and user interactions. The purpose is to provide an opportunity for people to present new work and early results, brainstorm different use cases, share best practices, and discuss the main challenges facing this line of research. - User Needs & Tasks Understanding: - User intent analysis/prediction - User goals & missions - Task identification - Task aware suggestions & recommendations - User Modeling & Personalization: - Short and Long-term User Modelling - Personalization - Diversification - Coherence - Metrics and Evaluation : - Metrics based on user interactions - User engagement metrics design - Evaluation mechanisms - User satisfaction prediction - Controlled laboratory study - Online metrics - Test collection - User Interaction Processes & Context : - User Journey Optimization - Evolution of search process - Stages of user interactions - User journey through the system - Leveraging contextual signals - Learning for user interaction optimization: algorithms, frameworks & system designs - Intelligent interface designs: - Adaptive personal digital assistants - Tailored decision support - Adaptive collaboration support - Applications: - Conversational search, chatbots, digital assistants - Contextual Advertising - E-commerce recommendations - Customer Support - Intelligent interfaces - Personal search - Case studies of real world implementations Submission All workshop submissions must be formatted according to ACM SIG Proceedings template. We welcome submissions in either long or short format spanning 4-6 pages. Authors should submit original papers in PDF format through the Easychair system . This is a workshop where discussion is central, and all attendees are active participants. The workshop will include keynote talks to set the stage and ensure all attendees are on the same page. A small number of contributed papers will be selected for short oral presentation (15-10 minutes), all other papers have a 2 minute boaster, and all papers are presented as poster in an interactive poster session. The results will be disseminated in various ways: - A high quality, peer reviewed workshop proceedings, published in the http://ceur-ws.org/ workshop proceedings series. - A report on the results of the workshop in the ACM SIGIR Forum of June 2018. - If the outcome lives up to our high expectations, we will consider a special issue in an appropriate journal. Important Dates - Submission Deadline: 30th November 2017 - Notification: 15th December 2017 - Workshop: 9th February 2018 Organizers 1. Rishabh Mehrotra (University College London) 2. Emine Yilmaz (University College London; The Alan Turing Institute) 3. Ahmed Hassan Awadallah (Microsoft Research) You can contact us at learnIRwrkshp at gmail.com . Steering Committee: - Milad Shokouhi (Microsoft) - Fernando Diaz (Spotify) - Filip Radlinski (Google Research) - Evangelos Kanoulas (University of Amsterdam) -- Rishabh. Web: www.rishabhmehrotra.com Github: https://github.com/rishabhmehrotra/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mgalle at gmail.com Tue Nov 21 15:04:46 2017 From: mgalle at gmail.com (=?UTF-8?Q?Matthias_Gall=C3=A9?=) Date: Tue, 21 Nov 2017 21:04:46 +0100 Subject: Connectionists: NaverLabs (Grenoble, France) recruits: NLP researchers, engineers, post-docs Message-ID: (apologies for cross-posting) Naver Labs (ex-Xerox Research Centre Europe) is expanding its NLP team. We are looking for post-docs, research scientist and research engineers. Job description and application guidelines can be found below. If your are in NLP (or in machine learning but really love text), are good, like to work in an industrial lab with real data but with an eye on the latest developments in academia (and contribute through publications and collaborations), then I would love to talk to you. Informal inquiries are welcome --mg http://www.europe.naverlabs.com/NAVER-LABS-Europe/Jobs/Natural-Language-Processing-Research-Engineer http://www.europe.naverlabs.com/NAVER-LABS-Europe/Jobs/Natural-Language-Processing-Researcher -------------- next part -------------- An HTML attachment was scrubbed... URL: From dengdehao at gmail.com Wed Nov 22 01:20:01 2017 From: dengdehao at gmail.com (Teng Teck Hou) Date: Wed, 22 Nov 2017 14:20:01 +0800 Subject: Connectionists: [INNS-BDDL 2018] Final Call for Papers Message-ID: <5a151712.8a1c6b0a.b9a8a.8202@mx.google.com> [Apologies for cross-postings] ########################################################### CALL FOR PAPERS The 3rd INNS Conference on Big Data and Deep Learning 2018 April 17-19, 2018, Bali, Indonesia Homepage: http://www.innsbigdata2018.org #######################Description:###################### The International Neural Network Society (INNS) is the premiere organization for individuals interested in a theoretical and computational understanding of the brain and applying that knowledge to develop new and more effective forms of machine intelligence. INNS was formed in 1987 by the leading scientists in the neural network field. Researchers and colleagues who work in the area of big data and machine learning, we are happy to announce "The 3rd INNS Conference on Big Data and Deep Learning (INNS BDDL) will be held Tuesday through Thursday, April 17 ? 19, 2018 at the Grand Inna Bali Beach hotel, Sanur, Bali, Indonesia. The INNS BDDL conference aims to create a valuable and important forum for scientists and engineers throughout the world to present the latest research findings and idea at the forefront of Big Data and Deep Learning." Accepted and presented papers will be published in Procedia Computer Science indexed by Scopus. Several papers will be selected for possible publication in a high-quality journal. A preliminary list of such journals includes: - Cognitive Systems Research (Scopus SJR 0.648, Impact Factor 1.182) - Cognitive Computation (Scopus SJR 0.823, Impact Factor 3.441) - Big Data Analytics - Evolving Systems (Scopus SJR 0.459, Impact Factor 1.067) - International Journal of Neural Systems (Scopus SJR 1.121, Impact Factor 6.333) - and possibly others Several papers will be selected for possible publication in top journals. The conference will feature a comprehensive technical program with technical tracks on: Track 1: Big Data Track 2: Big Data Algorithms Track 3: Deep Learning Track 4: Application Areas ####################Important Dates################################# * Tutorial and workshop proposals (Submission) ?30 September 2017 * Tutorial and workshop proposals (Decision) ? 7 October 2017 * Paper submission ???? 1 December 2017 * Decision notification???? 8 January 2018 * Camera-ready submission??? 2 February 2018 * Conference????? 17 - 19 April 2018 ################################################################### #########################Keynote Speakers########################## * Geoffrey I. Webb, Monash University, Australia * Kay Chen Tan, City University, Hong Kong * Ari Santoso, Ministry of Education and Culture ################################################################### #################### Organizing committees ############### General chairs Seiichi Ozawa, Kobe University, Japan Ah-Hwee Tan, Nanyang Technological University, Singapore Program Chairs Plamen P. Angelov, Lancaster University, UK Asim Roy, Arizona State University, USA Mahardhika Pratama, Nanyang Technological University, Singapore Honorary Board Mohammad Nuh, Institut Teknologi Sepuluh Nopember, Indonesia Joni Hermana, Institut Teknologi Sepuluh Nopember, Indonesia Heru Setyawan, Institut Teknologi Sepuluh Nopember, Indonesia Local Committee Chairs Dieky Adzkiya, Institut Teknologi Sepuluh Nopember, Indonesia Advisory Board Yew-Soon Ong, Nanyang Technological University, Singapore Robert Kozma, University of Memphis, USA Sankar K. Pal, Indian Statistical Institute, India Haibo He, University of Rhode Island, USA Witold Pedrycz, University of Alberta, Alberta, Canada Leszek Rutkowski, Czestochowa University of Technology, Poland Nikola Kasabov, Auckland University of Technology, New Zealand Fernando Gomide, University of Campinas, Brazil Marley Vellasco, Pontif?cia Universidade Cat?lica do Rio de Janeiro, Brazil Yoonsuck Choe, Texas A&M University Minho Lee, Kyungpook National University, South Korea Bao-Liang Lu, Shanghai Jiao Tong University, China Irwin King, the Chinese University of Hong Kong, Hong Kong Tutorials/Workshop Chairs Igor Skrjanc, University of Ljubljana, Slovenia Sundaram Suresh, Nanyang Technological University, Singapore Noor Akhmad Setiawan, Universitas Gadjah Mada, Indonesia Poster Sessions Chairs Eko Setiadji, Institut Teknologi Sepuluh Nopember, Indonesia Agus Salim, La Trobe University, Australia Ali Ridho Barakbah, Politeknik Elektronika Negeri Surabaya, Indonesia Special Sessions Chairs Justin Wang, La Trobe University, Australia Yongping Pan, National University of Singapore, Singapore Alfian Futhul Hadi, Universitas Jember, Indonesia Panel Chairs Sreenatha Anavatti, University of New South Wales, Australia Mukesh Prasad, University of Technology, Sydney, Australia Achmad Affandi, Institut Teknologi Sepuluh Nopember, Indonesia Awards Chairs Tapabrata Ray, University of New South Wales, Australia Dejan Dovzan, University of Ljubljana, Slovenia Richard J. Oentaryo, McLaren Applied Technologies, Singapore Publication Chairs Edwin Lughofer, Johannes Kepler University, Austria Jose Antonio Iglesias, Carlos III University of Madrid, Spain Moamar Sayed?Mouchaweh, Institute Mines Telecom Lille Douai, France Publicity Chair Simone Scardapane, Sapienza University, Italy Teng Teck Hou, Singapore Management University, Singapore Kurnianingsih, Politeknik Negeri Semarang, Indonesia International Liaison Chairs Yun Sing Koh, University of Auckland, New Zealand Deepak Puthal, University of Technology Sydney, Australia Wirawan, Institut Teknologi Sepuluh Nopember, Indonesia Webmaster Mohamad Abdul Hady, Institut Teknologi Sepuluh Nopember, Indonesia Andri Ashfahani, Institut Teknologi Sepuluh Nopember, Indonesia Choiru Za?in, La Trobe University, Australia ########################################################## ###### Topics and Areas include, but not limited to the following###### >>BIG DATA Autonomous, online, incremental learning in big data High dimensional data, feature selection, feature transformation for big data Scalable algorithms for big data Big data analytics Data stream analytics Parallel & distributed computing for big data analytics (cloud, map-reduce, etc.) Online learning Online multimedia/stream/text analytics Link and graph mining Big data and cloud computing, large scale stream processing on the cloud Big data and collective intelligence/collaborative learning Big data and hybrid systems Big data and self-aware systems Big data and infrastructure Big data visualization? >>Big Data Algorithm Neuromorphic hardware for scalable machine learning Evolving systems for big data analytics Evolutionary systems and big data Fuzzy systems and big data Cognitive modelling and big data Probabilistic approach for big data Concept drift detection for big data Granular computing for big data Transfer learning for big data >>Deep Learning Deep belief network Convolutional neural network Long short term memory Deep network architecture Deep autoencoder Deep stacked network Deep learning for natural language processing Deep learning for machine vision Evolving deep network Transfer learning in deep learning Online deep learning >>Application Areas Banking and Securities Communications, Media and Entertainment Healthcare Providers Education Manufacturing & Natural Resources Government Insurances Retail & Wholesale Trade Transportation Energy & Utilities, Etc. ############################################################################ ##########################Sponsoring Organizations################# * INNS - International Neural Network Society * MTC - Mechatronic Technology Center, Institut Tecknologi Sepuluh Nopember ################################################################ Previous INNS Conference: INNS 2016 in Thessaloniki, Greece INNS 2015 in San Francisco, USA -------------- next part -------------- An HTML attachment was scrubbed... URL: From rsalakhu at cs.toronto.edu Tue Nov 21 18:01:48 2017 From: rsalakhu at cs.toronto.edu (rsalakhu at cs.toronto.edu) Date: Tue, 21 Nov 2017 18:01:48 -0500 Subject: Connectionists: ICML 2018: Call for Tutorial Proposals Message-ID: <6fb3d9f9dabdaed2e6360002b560c3f8.squirrel@webmail.cs.toronto.edu> The ICML 2018 Organizing Committee invites proposals for tutorials to be given on July 10th, 2018, immediately preceding the main conference. We welcome proposals for tutorials on either core machine learning topics or topics of emerging importance for machine learning. We will consider tutorials on any topic if the proposal makes a strong argument that such a tutorial serves an important function for the ICML community. Tutorials should be of interest to a substantial part of the ICML audience and represent a sufficiently mature area of research or practice. We anticipate to accept nine tutorials, running three in parallel; each tutorial will be 2 hours long. Proposals should be structured to answer the following questions: 1) Title 2) Brief description and outline: What will the tutorial be about? Please include a detailed outline of what you plan to cover. If available, please include samples of your past tutorial slides and links to video recordings on the topic. 3) Goals: What objectives does the tutorial serve? Why is it important to include it as a part of ICML-2018? 4) Target audience: Who is your target audience? How many participants do you expect to see? What kind of background do you expect them to have? 5) Presenters: Please include the names and email addresses of the presenters, along with brief bios. Since time is short, we suggest that each tutorial is given by at most two presenters. If there is more than one presenter, please describe how time will be split. Please briefly describe each presenter?s expertise in the tutorial area. Tutorial proposals should be submitted to tutorial at icml.cc by March 2, 2018. Tutorial Chairs, ICML 2018 Arthur Gretton and Ruslan Salakhutdinov From robert.jenssen at uit.no Wed Nov 22 10:14:03 2017 From: robert.jenssen at uit.no (Robert Jenssen) Date: Wed, 22 Nov 2017 15:14:03 +0000 Subject: Connectionists: 1st Northern Lights Deep Learning Workshop In-Reply-To: <1510645313264.70793@uit.no> References: <1502093829881.59265@uit.no>,<1510645313264.70793@uit.no> Message-ID: <1511363643286.91003@uit.no> We are extending the call for contributions: New deadline 29th Nov. for the 1st Northern Lights Deep Learning Workshop 10-11 January 2018, Tromso, "North Pole", Norway. Please see nldl2018.org for more info. Registrations will soon open soon.? Thanks! Robert Jenssen Michael Kampffmeyer Arnt-Borre Salberg -------------- next part -------------- An HTML attachment was scrubbed... URL: From D.G.HEINKE at bham.ac.uk Wed Nov 22 10:34:20 2017 From: D.G.HEINKE at bham.ac.uk (Dietmar Heinke) Date: Wed, 22 Nov 2017 15:34:20 +0000 Subject: Connectionists: PhD position in computational modelling of EEG Message-ID: <06D3DF7C411486418BEF3DCBF554BFAF01BC2BEAAA@EX13.adf.bham.ac.uk> PhD position: Computational modelling of EEG data from visual scene analysis Centre for Computational neuroscience and Cognitive Robotics, University of Birmingham, UK Contemporary EEG techniques focus on a range of statistical methods, such as fitting general linear models, correlations, time-frequency analysis, dynamic causal models, etc. However, there has been less work on connecting EEG signals directly to computational models of cognitive abilities. Such models are similar to methods in artificial intelligence (AI) which aim at mimicking human cognitive abilities (e.g. playing and winning the ancient board game, GO). The aim of this PhD project is to develop a novel method that tests such computational models by benchmarking them against EEG signals. In other words, this novel method will allow us to establish more directly links between human cognition and EEG signals than contemporary EEG methods. Consequently, we will be able to advance our understanding of neural mechanisms underlying cognitive abilities. As a test case for the new method the project will use the human visual system. Further information can be found here: https://warwick.ac.uk/fac/cross_fac/mibtp/pgstudy/phd_opportunities/neuroscience2018/cognitive Applicants should have a background in computational modelling, neuroscience, computer science, psychology, physics or related areas. Prior experience in statistical analysis and/or machine learning would be an advantage. The project will be based at the School of Psychology and the Computational Neuroscience and Cognitive Robotics Centre of the University of Birmingham, UK. The centre provides an excellent multidisciplinary, interactive and collaborative research environment combining expertise in cognitive neuroimaging, psychophysics and computational neuroscience. The psychology department was rated 5th in the UK research assessment exercise. The application deadline is the 7th January 2018. The starting date is Sept/Oct 2018. For further information click on https://www2.warwick.ac.uk/fac/cross_fac/mibtp/pgstudy/phd_opportunities/application/ or email: Dr Dietmar Heinke, d.g.heinke at bham.ac.uk From weixu at cse.ohio-state.edu Wed Nov 22 10:35:43 2017 From: weixu at cse.ohio-state.edu (Xu, Wei) Date: Wed, 22 Nov 2017 15:35:43 +0000 Subject: Connectionists: NAACL 2018 Student Research Workshop (SRW) - 2nd Call for Papers Message-ID: <100E9C38-2F8E-405E-B59B-3F61F9C6C760@osu.edu> ********************************************************************************************** ### NAACL 2018 Student Research Workshop (SRW) - 2nd Call for Papers ### ********************************************************************************************** The SRW workshop will be held in conjunction with NAACL HLT 2018 in New Orleans, Louisiana. Main conference: June 2-4, 2018 Student Research Workshop Paper Submission Deadline: March 02, 2018 (11:59pm PST) ------------------------------------------------------------------------------------------------------------------------------------------ *** Updates in 2nd Call: Pre-submission mentoring details, new ACL submission policy concerning arXiv, citation, and anonymity *** ### General Invitation for Submission #### The Student Research Workshop (SRW) provides a venue for student researchers to present their work in computational linguistics and natural language processing. Students receive feedback from the general conference audience as well as from mentors specifically assigned according to the topic of their work. We invite papers in two different categories: * Thesis Proposals: This category is appropriate for advanced students who have decided on a thesis topic and wish to get feedback on their proposal and broader ideas for their continuing work. * Research Papers: Papers in this category can describe completed work, or work in progress with preliminary results. For these papers, the first author must be a current graduate or undergraduate student. Topics of interest for the SRW are the same as NAACL main conference. See the list of topics at http://naacl2018.org/call_for_paper.html. Benefits of participation ------------------------------- * All accepted papers will be presented in the main conference poster session, giving students an opportunity to interact with and present their work to a large and diverse audience, including top researchers in the field. * All accepted thesis proposals will be presented during a session at the main conference, giving students an opportunity to receive feedback from assigned mentors and other researchers. * All accepted papers will be published in the NAACL 2018 SRW Proceedings. * Each participant is also assigned a mentor---an experienced researcher---who can provide valuable advice on the submission during the pre-submission period and mentoring during the conference. Important Dates --------------------- * Submission for mentoring deadline: January 15, 2018 * Papers submission deadline: March 02, 2018 * Acceptance notification deadline: April 02, 2018. * Camera-ready papers due: April 16, 2018. All deadlines are calculated at 11:59 pm (PST/GMT -8 hours) Submission Requirements ----------------------------------- All papers should follow the two-column format of the NAACL HLT 2018 proceedings (available here http://naacl.org/naacl-pubs/). All papers will have a maximum limit of 6 pages for content, with unlimited additional pages for references. Papers which do not conform to these specifications will be rejected without review. Submissions must conform to the specifications of NAACL HLT 2018 call for papers regarding multiple submissions and preparing papers for the double-blind review process. Use the Softconf link below for submission: https://www.softconf.com/naacl2018/naacl2018-SRW *** Updates *** * New ACL policies for concerning arXiv, citation, and anonymity: https://www.aclweb.org/portal/content/new-policies-submission-review-and-citation * Pre-submission mentoring details available in the website: https://naacl2018-srw.github.io/mentoring/ Grants ---------- We expect to have grants to offset some portion of the students' conference registration, travel and accommodation expenses. Further details will be posted in the SRW website. Contact Information --------------------------- The co-chairs of the workshop can be contacted by email at: naacl2018-srw at googlegroups.com. More details will be posted at the workshop website: https://naacl2018-srw.github.io. Student Chairs: * Silvio Ricardo Cordeiro (Federal University of Rio Grande do Sul) * Shereen Oraby (University of California, Santa Cruz) * Umashanthi Pavalanathan (Georgia Institute of Technology) * Kyeongmin Rim (Brandeis University) Faculty Advisors: * Sam Bowman (New York University) * Swapna Somasundaran (ETS Princeton) -------------- next part -------------- An HTML attachment was scrubbed... URL: From eneftci at uci.edu Wed Nov 22 12:49:01 2017 From: eneftci at uci.edu (Emre Neftci) Date: Wed, 22 Nov 2017 09:49:01 -0800 Subject: Connectionists: 2018 Telluride Neuromorphic Cognition Engineering Workshop Call for Topic Proposals: Deadline 21.12.2017 Message-ID: <1511372941.3522613.1181293408.336BCF14@webmail.messagingengine.com> The 2018 Telluride Neuromorphic Cognition Engineering Workshop is now accepting proposals for topic areas. The 2018 theme for the workshop is Embodied Perception and Cognition. Deadline for proposals is 21.12.2017. See the call here: https://docs.google.com/document/d/11tdwIIcJ75NagH5ENyQrG05z2pGKEt9EGRTOSWBoxC8/edit?usp=sharing We look forward to your proposals. Regards, The 2018 Telluride Workshop Organizing Team -- Emre Neftci, PhD, Assistant Professor, Neuromorphic Machine Intelligence Lab (http://nmi-lab.org/), Department of Cognitive Sciences, 2308 Social & Behavioral Sciences Gateway Building, UC Irvine 92697-5100 From dengdehao at gmail.com Wed Nov 22 19:59:44 2017 From: dengdehao at gmail.com (Teng Teck Hou) Date: Thu, 23 Nov 2017 08:59:44 +0800 Subject: Connectionists: [WCCI 2018 Special Session] Interpretable Deep Learning Classifiers Message-ID: <5a161d81.495d650a.2841.86f0@mx.google.com> [Apologies for cross-postings] Special Session on Interpretable Deep Learning Classifiers IEEE World Congress on Computational Intelligence 8 - 13 July 2018, Rio de Janeiro, Brazil www.ieee-wcci.org Chairs: Plamen P. Angelov, Lancaster University, UK p.angelov at lancaster.ac.uk Jose C. Principe, University of Florida, principe at cnel.ufl.edu Synopsis: Deep Learning is becoming a synonym of highly precise (reaching or surpassing capabilities of a human) computational intelligence technique. Very interesting and important results were reported recently in both scientific literature and also grabbed the imagination of the wider public and industry helping propel the interest towards AI, neural networks, machine learning. It was applied mostly to solve classification problems in image processing, but also for predictive tasks in speech processing and other problems. Despite the undoubted success in achieving high precision and avoiding handcrafting in feature selection a number of issues remain unresolved, such as: i) transparency and interpretability; ii) the requirement for extremely large training data set, computational resources and time; iii) overfitting and catastrophic failures with high confidence in some cases; iv) convergence proof for the case of reinforcement learning; v) rigid structure unable to be adapted/to dynamically evolve with new samples and/or new classes; vi)repeatability of the results. Methodologically, the vast majority of the techniques of this hot and quickly developing area are based exclusively on neural networks (convolutional, belief based, etc.). Very recently publications appear where the deep learning (multi-layer) architecture with different levels of abstraction is build based on fuzzy rulebased systems or fuzzy sets are used to represent coefficients/weights in Restricted Bolzman Machines, etc. The aim of the special session is to address the bottleneck issues listed above and discuss and represent alternative and most recent methods, techniques and approaches that can help resolve these issues. The specific sub-topics that will be of interest include: * Interpretable/Transparent Deep Learning * Computational and time complexity/efficiency of Deep Learning Methods * Repeatability of the results of Deep Learning Methods * Degree of confidence in the results of Deep Learning * Highly Parallelisable Deep Learning Methods * Deep Learning with proven convergence * Re-trainability and dynamically evolving structures/architectures for Deep Learning * Ensembles of Deep Learning Classifiers * Fuzzy Deep Rule-based Classifiers * Self-adaptive and Self-organising Deep Learning Architectures Also applications to: * Computer Vision * Image Classification * Robotics * Remote Sensing * Biology and Tomography * Surveillance and Defense * Industry 4.0 * Assistive Technologies and Digital Health Important dates: * Paper Submission Deadline 15 January, 2018 * Paper acceptance notification date 15 March, 2018 * Final paper submission deadline 1 May, 2018 Conference: 8-13 July, 2018 Submission Guidelines: Please follow the regular submission guidelines of WCCI 2018. Please notify the chairs of your submission by sending an email to: p.angelov at lancaster.ac.uk or principe at cnel.ufl.edu This special session is supported by the IEEE Task Forces on Deep Learning http://deeplearning.math.unipd.it/ and on Evolving and Adaptive Fuzzy Systems, http://www.caos.inf.uc3m.es/aefs/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From stefanos at cs.ntua.gr Thu Nov 23 11:44:05 2017 From: stefanos at cs.ntua.gr (Stefanos Kollias) Date: Thu, 23 Nov 2017 18:44:05 +0200 Subject: Connectionists: post doc position advertised Message-ID: Dear colleagues, Please find below the advertisement link of an about 3 year post-doc position at the University of Lincoln, UK, ready to start, focusing on machine learning and analysis of agricultural data, data storage in cloud environment, and decision support post-activities. This post refers to an EU Project collaboration (SmartGreen Project, 2017-2021) : https://jobs.lincoln.ac.uk/vacancy.aspx?ref=COS471 . Kind regards Stefanos Kollias -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.herbster at cs.ucl.ac.uk Thu Nov 23 21:58:48 2017 From: m.herbster at cs.ucl.ac.uk (Mark Herbster) Date: Fri, 24 Nov 2017 02:58:48 +0000 Subject: Connectionists: Research Associate Position in in Graph-based Machine Learning Message-ID: <4ABEC44B-4FD9-431D-8F79-DB4EF5F774FE@cs.ucl.ac.uk> Research Associate Position in Graph-based Machine Learning University College London Department of Computer Science The aim of this 16 month Research Associate position is to design and analyse efficient algorithms for Graph-based machine learning. We are interested in problems such as but not limited to semi-supervised learning, spectral clustering, graph bandits, community detection, and graph homeomorphism. The postdoc will be carried out in collaboration with Braintree UK. Braintree is developing a modular platform to exploit graph-based data for Machine Learning. The RA will have the opportunity to collaborate with Braintree on the implementation of the considered algorithms. The successful candidate will have a PhD in Mathematics, Computer Science or Physics, with ideally an emphasis on Machine Learning. Experience in proving performance guarantees in both the online and batch settings as well as programming experience in Neo4j and Java is valuable. To apply, see https://atsv7.wcn.co.uk/search_engine/jobs.cgi?owner=5041404&ownertype=fair&jcode=1690777&vt_template=965&adminview=1 Please contact Mark Herbster (m.herbster at cs.ucl.ac.uk) for additional information. From Tony.Pipe at brl.ac.uk Fri Nov 24 04:11:21 2017 From: Tony.Pipe at brl.ac.uk (Tony Pipe) Date: Fri, 24 Nov 2017 09:11:21 +0000 Subject: Connectionists: Professor of Robotics In-Reply-To: <5710AC8D.6000205@brl.ac.uk> References: <5710AC8D.6000205@brl.ac.uk> Message-ID: <2db371ad-8c8f-fb5c-b8df-4eaf200976b8@brl.ac.uk> Job title: Professor of Robotics Department: Bristol Robotics Laboratory Campus/location: Frenchay, Bristol campus Salary band: ?60,173 - ?86,889 per annum Duration of post: Permanent Closing date: 19 January 2018 @ 23:59 Job Overview: The Bristol Robotics Laboratory at the Faculty of Environment & Technology have an exciting permanent and full time position for a Professor of Robotics to join BRL within the Engineering, Design & Mathematics Department. The Robotics and Autonomous Systems (RAS) research-and-innovation pipeline is now experiencing unprecedented growth, evidenced by substantial new research opportunities appearing across the UK, EU and global funding landscape. In the context of Human-Robot Interaction, you will champion research in control systems underpinning: 1. advanced augmented and virtual reality via immersive tele-operation; 2. dynamic Levels of Autonomy (LoA) , typically varying from teleoperation to autonomous control, i.e., the ability to dynamically switch between different LoA so as to significantly outperform any single Level. These research topics can lead naturally to shared control frameworks that enable both human and AI to collaborate in controlling one or more robots, thus simultaneously fusing reasoning from both the human and the autonomous agent. These methods are particularly relevant to safety-critical application domains where remote operation and varying autonomy could be highly beneficial. This strategic focus resonates strongly as a fundamental and core issue in domains that stretch from assisted living, through robot-assisted surgery, to operations in an array of challenging and/or hazardous environments (e.g. nuclear decommissioning, subsea, space, offshore maintenance), and human-robot teamwork in manufacturing domains that incorporate critical elements of ?Industrie 4.0?. In all of these areas, a human-in-the-loop may be required for some or even all of the time, but complex manipulations may be too difficult to directly teleoperate efficiently. We are looking for a candidate that could take on the challenge of joining these common factors across the application domains, all of which are existing foci for BRL, i.e., a candidate who will work with and grow our existing teams as part of our BRL Unique Selling Point. We welcome applications from researchers able to build on strongly linked disciplines and who are fully committed to developing one or more of the area of research outlined above. UWE Bristol is an ambitious university. Together, our people are working hard to advance knowledge, inspire people and transform futures. We are looking for people with the skills and ambition to help us achieve those aims. We are a well-established university, with over 27,000 students, 250,000 alumni and 3,000 staff. Students come to study with us from all over the UK, as well as from 140 different countries around the world, making this a diverse and interesting place to come and study. Bristol itself is a hub of social and cultural activity. A place with a strong, creative and fiercely independent mindset. A city with a buzzing music scene, great restaurants and interesting business ventures. It?s not surprising Bristol is consistently named as one of the best places to live and work in the UK. In addition to progressive pay rates, UWE Bristol offers a wide range of staff benefits including: * a generous holiday allowance of 35 Days * up to 12.5 bank holiday/closure days per year in addition; * flexible working; * excellent defined benefit pension schemes; * option to participate in the cycle to work scheme; * family friendly policies; * onsite nursery at our Frenchay Campus; * option to purchase childcare vouchers. This post is based at our lively Frenchay campus where we have invested in the latest facilities and resources to give our students access to everything they need to succeed ? with ?300m being spent on new state-of-the-art learning spaces and accommodation between now and 2020 to enhance our offer even further. Frenchay campus is within close proximity to excellent motorway links and within walking distance of two train stations, making UWE Frenchay Campus the ideal place to work for those wishing to commute to Bristol. If you have any queries or would like an informal discussion, please contact the Director of BRL, Prof. Chris Melhuish at Chris.Melhuish at uwe.ac.uk or on +44 117 328 6332. Link to Bristol Robotics Laboratory with more details of the laboratory and full advert is: http://www.brl.ac.uk (http://www.brl.ac.uk/jobsatbrl.aspx for advert only). Alternative link for more details of the role and how to apply, please visit: https://atsv7.wcn.co.uk/search_engine/jobs.cgi?amNvZGU9MTY5MzczMiZvd25lcj01MDU1Mjc4Jm93bmVydHlwZT1mYWlyJnBvc3RpbmdfY29kZT00OTcmdnRfdGVtcGxhdGU9MTUzOA&jcode=1693732&owner=5055278&ownertype=fair&posting_code=497&vt_template=1538 -- > Tony Pipe > Professor of Robotics and Autonomous Systems > Deputy Director: Bristol Robotics Laboratory > > Bristol Robotics Laboratory > T-Building > Frenchay Campus > Bristol UK BS16 1QY > Tel: +44 (0)117 3286330 -- Tony Pipe Professor of Robotics and Autonomous Systems Deputy Director: Bristol Robotics Laboratory Bristol Robotics Laboratory T-Building Frenchay Campus Bristol UK BS16 1QY Tel: +44 (0)117 3286330 -------------- next part -------------- An HTML attachment was scrubbed... URL: From compsens at medizin.uni-tuebingen.de Fri Nov 24 07:02:08 2017 From: compsens at medizin.uni-tuebingen.de (Compsens) Date: Fri, 24 Nov 2017 13:02:08 +0100 Subject: Connectionists: =?utf-8?q?PhD_Position=3A_Deep_learning_architect?= =?utf-8?q?ures_for_hierarchical_motor_control=2C_=28T=C3=BCbingen=29=2C_G?= =?utf-8?q?ermany?= Message-ID: <20171124130208.Horde.BeOh9wEAa3A3mxaZ-g3PP71@webmail.uni-tuebingen.de> PHD POSITION: DEEP LEARNING ARCHITECTURES FOR HIERARCHICAL MOTOR CONTROL (Hertie Institute / Center for Integrative Neuroscience, University of Tuebingen, Germany) The Section for Computational Sensomotorics at the Center for Integrative Neurosciences (CIN) and the Hertie Institute for Clinical Brain Research (HIH) at the University of Tuebingen invites applications for a PhD student for a project on the learning of hierarchical neural models for motor control. The position is funded for duration of 3 years within a collaborative project with M.I.T. (Cambridge, MA), the Weizmann Institute (Rehovot, Israel), and Northeastern University (Boston, USA). We offer employment with salary (E13/14, 60%) and social benefits based on German DFG standards. The goal of the project is to develop biologically-inspired machine-learning models for hierarchical representations in motor control, specifically exploiting new techniques from the field of Deep Learning. What we offer: ?being part of an inspiring multidisciplinary and international research team ?possibility to obtain a PhD in Neuroscience at the International Graduate Training Center for Neuro-science in Tuebingen or of a PhD in Computer Science at Tuebingen University ?specialized courses, summer schools, seminars by renowned experts ?stimulating interdisciplinary scientific environment (HIH among top 3 European institutions for clinical brain research; Bernstein Center for Computational Neuroscience; 3 Max Planck Institutes: Biological Cybernetics, Intelligent Systems, and Developmental Biology). ?active participation at international conferences ?collaborations with leading international partners in neuro- and computer science (including M.I.T, KU Leuven, Imperial College, CALTECH, etc.) What we are looking for: ?person with Master degree in Computational Neuroscience or a related discipline (Computer Science, Engineering, Physics, Mathematics, Cognitive Science, Mathematical Psychology, etc.) ?enthusiasm for research ?strong mathematical background and basic programming skills (at least in C++ , MATLAB or Python); willingness to learn relevant techniques and software for deep learning, and the simulation of biological neurons ?interest in motor control and related technical applications ?English speaking and writing skills. Committed to Equal Opportunities. Interested candidates should send their application, including a CV, all marks from studies, 2 letters of reference, and a short research statement of about one half page (explaining how your skills might support a project on learning of hierarchies in motor control) to: ------------------------------------------------------------------------------ Prof. Dr. Martin Giese Section for Theoretical Sensomotorics, Dept. for Cognitive Neurology Hertie Institute for Clinical Brain Research & Center for Integrative Neuroscience University of Tuebingen, Otfried-M?ller Str. 25, D-72076 Tuebingen GERMANY Tel.: +49 7071 2989124 Email: martin.giese at uni-tuebingen.de Web: http://www.compsens.uni-tuebingen.de/ From compsens at medizin.uni-tuebingen.de Fri Nov 24 06:57:19 2017 From: compsens at medizin.uni-tuebingen.de (Compsens) Date: Fri, 24 Nov 2017 12:57:19 +0100 Subject: Connectionists: =?utf-8?q?PhD_Position_in_neuroscience/_computati?= =?utf-8?q?onal_neuroscience_=28T=C3=BCbingen=29=2C_Germany?= Message-ID: <20171124125719.Horde.DdciCOlQfIpA869ytQqp0Zy@webmail.uni-tuebingen.de> PHD POSITION: COMPUTER ANIMATION AND MACHINE LEARNING TECHNOLOGY FOR THE STUDY OF ACTION AND SOCIAL PERCEPTION (Hertie Institute / Center for Integrative Neuroscience, University of Tuebingen, Germany) The Section for Computational Sensomotorics at the Center for Integrative Neurosciences (CIN) and the Hertie Institute for Clinical Brain Research (HIH) at the University of Tuebingen invites applications for a PhD student for a project that aims at the development of novel technology for the study of action and social perception exploiting VR technology. VR and computer animation combined with state-of-the-art machine learning approaches (including deep learning) offer novel possibilities for the investigation and understanding of the neural basis of the perception of actions and social signals. The project aims at the development of novel learning-based technologies combining state-of-the-art learning technology and computer graphics for the study of social perception exploiting facial and body movements in humans and animals, including clinical applications. The project is funded for duration of 3 years. What we offer: ?being part of an inspiring multidisciplinary and international research team ?possibility to obtain a PhD in Neuroscience at the International Graduate Training Center (GTC) for Neuro-science in Tuebingen or of a PhD in Computer Science at Tuebingen University ?specialized courses, summer schools, seminars by renowned experts at the GTC ?stimulating interdisciplinary scientific environment (HIH among top 3 European institutions for clinical brain research; Bernstein Center for Computational Neuroscience; 3 Max Planck Institutes: Biological Cybernetics, Intelligent Systems, and Developmental Biology). ?active participation at international conferences ?collaborations with leading international partners in neuro- and computer science (including M.I.T, KU Leuven, Imperial College, CALTECH, etc.) What we are looking for a person with: ?a Master degree in Computer Science, Engineering, Physics, mathematics, or Computational Neuroscience or a related discipline ?strong motivation and enthusiasm for research, ?strong mathematical background ?programming skills (at least in C++ , MATLAB or Python), ideally some knowledge in Computer Graphics, Computer Vision or VR ?willingness to learn relevant techniques and software tools for computer animation, computer vision and deep learning ?interest in action and social perception, related technical and neuroscience applications ?English speaking and writing skills. Committed to Equal Opportunities. Interested candidates should send their application, including a CV, all marks from studies, 2 letters of reference, and a short research statement of about one half page (explaining how your skills might support a project on learning of hierarchies in motor control) to: ------------------------------------------------------------------------------ Prof. Dr. Martin Giese Section for Theoretical Sensomotorics, Dept. for Cognitive Neurology Hertie Institute for Clinical Brain Research & Center for Integrative Neuroscience University of Tuebingen, Otfried-M?ller Str. 25, D-72076 Tuebingen GERMANY Tel.: +49 7071 2989124 Email: martin.giese at uni-tuebingen.de Web: http://www.compsens.uni-tuebingen.de From compsens at medizin.uni-tuebingen.de Fri Nov 24 07:06:44 2017 From: compsens at medizin.uni-tuebingen.de (Compsens) Date: Fri, 24 Nov 2017 13:06:44 +0100 Subject: Connectionists: =?utf-8?q?Postdoc_/_phd_position=3A_VR_and_robot_?= =?utf-8?q?technology_for_rehabilitation_training_in_neurological_disoders?= =?utf-8?b?IChUw7xiaW5nZW4pLCBHZXJtYW55?= Message-ID: <20171124130644.Horde.3XmUZNPvdkM3BbjY_sPVFwB@webmail.uni-tuebingen.de> POSTDOC / PHD POSITION: VR AND ROBOT TECHNOLOGY FOR REHABILITATION TRAINING IN NEUROLOGICAL DISOREDERS (CIN, HIH, University Clinic Tuebingen, Germany) ============================================================ The Section for Computational Sensomotorics at the Center for Integrative Neurosciences and the Hertie Institute for Clinical Brain Research and the Centre of Integrative Neuroscience at the University of Tuebingen invites applications for a 2y-Postdoc or a 3y PhD student in the field of biomedical engineering. The position is funded within the EC research project COGIMON. This highly interdisciplinary project aims at the development of new VR and humanoid robot technology including biologically- inspired control algorithms for applications including rehabilitation training in patients. The available project focuses on the development of VR technology in combination with machine learning, including the use of inertial sensor systems and establishing links to humanoid robots for applications in rehabilitation training. We offer employment with salary and social benefits based on the collective agreement for public service employees in the academic and science sector in Germany. What we offer: ?being part of an inspiring multidisciplinary and international research team ?possibility to obtain a PhD in theoretical Neuroscience at the International Graduate Training Center for Neuroscience in Tuebingen or of a PhD in Computer Science at Tuebingen University ?specialized courses, summer schools, seminars by renowned experts ?stimulating interdisciplinary scientific environment (HIH among top 3 European institutions for clinical brain research; Bernstein Center for Computational Neuroscience; 3 Max Planck Institutes: Biological Cybernetics, Intelligent Systems, and Developmental Biology). ?active participation at international conferences ?collaborations with leading international partners in neuro- and computer science (including M.I.T, KU Leuven, Imperial College, IIT, CALTECH, etc.) What we are looking for: ?person with Master degree in Computer Science, Engineering, Physics, Mathematics, or Computational Neuroscience or a related discipline ?enthusiasm for research and independent problem solving ?strong mathematical background and basic programming skills (at least in C++ , MATLAB or Python) ?willingness to learn relevant techniques and software for VR and machine learning ?interest in biomedical engineering, VR and robotics ?English speaking and writing skills Committed to Equal Opportunities. Interested candidates should send their application, including a CV, all marks from studies, 2 letters of reference, and a short research statement of about one half page (explaining how your skills might support a project on learning of hierarchies in motor control) to: ------------------------------------------------------------------------------ Prof. Dr. Martin Giese Section for Theoretical Sensomotorics, Dept. for Cognitive Neurology Hertie Institute for Clinical Brain Research & Center for Integrative Neuroscience University of Tuebingen, Otfried-M?ller Str. 25, D-72076 Tuebingen GERMANY Tel.: +49 7071 2989124 Email: martin.giese at uni-tuebingen.de Web: http://www.compsens.uni-tuebingen.de/ From luca.oneto at unige.it Sat Nov 25 06:18:25 2017 From: luca.oneto at unige.it (Luca Oneto) Date: Sat, 25 Nov 2017 12:18:25 +0100 Subject: Connectionists: ESANN 2018 SS Final CPF - Emerging trends in machine learning: beyond conventional methods and data Message-ID: [Apologies if you receive multiple copies of this CFP] Call for papers: special session on "Emerging trends in machine learning: beyond conventional methods and data" at ESANN 2018 European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018). 25-27 April 2018, Bruges, Belgium - http://www.esann.org DESCRIPTION: Recently, new promising theoretical results, techniques, and methodologies have attracted the attention of many researchers and have allowed to broaden the range of applications in which machine learning can be effectively applied in order to extract useful and actionable information from the huge amount of heterogeneous data produced everyday by an increasingly digital world. Examples of these methods and problems are: - Learning under privacy and anonymity constraints - Learning from structured, semi-structured, multi-modal (heterogeneous) data - Constructive machine learning, e.g. generative models and structured output learning - Reliable machine learning - Learning to learn, e.g. lifelong learning and learning the loss - Mixing deep and structured learning, e.g. mixture of wide and deep models - Semantics-enabled recommender systems - Reproducibility and interpretability in machine learning - Human in the loop - Adversarial learning The focus of this special session is to attract both solid contributions or preliminary results which show the potentiality and the limitations of new ideas, refinements, or contaminations between the different fields of machine learning and other fields of research in solving real world problems. Both theoretical and practical results are welcome to our special session. SUBMISSION: Prospective authors must submit their paper through the ESANN portal following the instructions provided in https://www.elen.ucl.ac.be/esann /index.php?pg=submission. Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers. IMPORTANT DATES: Submission of papers: *29 November 2017* Notification of acceptance: 31 January 2018 ESANN conference: 25-27 April 2018 SPECIAL SESSION ORGANISERS Luca Oneto , University of Genoa (Italy) Nicol? Navarin , University of Padua (Italy) Michele Donini , Istituto Italiano di Tecnologia (Italy) Davide Anguita , University of Genoa (Italy) ------------------------------------------------------------ ----------------------- Luca Oneto, PhD University of Genoa web: www.lucaoneto.com DIBRIS Department e-mail: Luca.Oneto at unige.it SmartLab Laboratory e-mail: Luca.Oneto at gmail.com Via Opera Pia 11a Fax: +39-010-3532897 <+39%20010%20353%202897> 16145 Genoa ITALY Phone: +39-010-3532192 <+39%20010%20353%202192> www.smartlab.ws ------------------------------------------------------------ ----------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From mfasli at essex.ac.uk Sun Nov 26 12:42:34 2017 From: mfasli at essex.ac.uk (Fasli, Maria) Date: Sun, 26 Nov 2017 17:42:34 +0000 Subject: Connectionists: RCUK Innovation Fellowship, University of Essex Message-ID: Apologies for cross postings *** RCUK Innovation Fellowship *** 3 year post, ?39,993-?41,212 per annum Institute for Analytics and Data Science University of Essex, UK Closing Date: 15 December 2017 The University of Essex (UK) is currently advertising an RCUK Innovation Fellowship (3 years) in the Institute for Analytics and Data Science (IADS) on ?Discovering Individual and Social Preferences through Inverse Reinforcement Learning?. Appointment to this post will be made as Research Fellow. The main duties of the post include to undertake foundational and applied Research and high quality independent and collaborative research within the scope of the RCUK Innovation Fellowship that meets REF standards. Other duties include to contribute to Public Engagement & Impact such as community engagement and interactions with other public sector bodies, business and the third sector. The candidate will be required to comply with the conditions of the RCUK Fellowship (for more details see job specification). Applicants are also required to have a PhD in Quantitative Social Science, Computer Science, Artificial Intelligence, Data Science, Statistics, or related discipline, or related professional experience. Candidates should have a maximum of four years academic research experience following the submission of their PhD, or be of equivalent professional standing. Particular research areas of interest include but are not limited to: - quantitative methods; - advanced statistical methods; - machine learning; - reinforcement learning; - social preference and social choice. For more information and to make an application, please see here: https://vacancies.essex.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID=794034FJJf&WVID=9918109NEm&LANG=USA The job specification can be found here: https://www1.essex.ac.uk/hr-jobpacks/science_health-csee/REQ01033_Jobpack.pdf Informal enquiries can be directed to Prof Maria Fasli (mfasli at essex.ac.uk). Professor Maria Fasli PhD, NTF, FHEA UNESCO Chair in Analytics and Data Science Director, Institute for Analytics and Data Science University of Essex T +44 (0)1206 872327 E mfasli at essex.ac.uk Follow us on Twitter @EssexIADS PA Shaaba Lotun T +44 (0)1206 873496 E slotun at essex.ac.uk ? http://www.essex.ac.uk/iads/ WE ARE ESSEX TOP 20 FOR RESEARCH EXCELLENCE From mfasli at essex.ac.uk Sun Nov 26 12:47:27 2017 From: mfasli at essex.ac.uk (Fasli, Maria) Date: Sun, 26 Nov 2017 17:47:27 +0000 Subject: Connectionists: Research Fellow post in Machine Learning (leading to permanent academic position) Message-ID: Apologies for cross postings ***Postdoctoral Research Fellow Post in Machine Learning/Artificial Intelligence*** 3-year post leading to permanent academic (Lecturer) position ?32,548 - ?38,832 per annum Institute for Analytics and Data Science University of Essex, UK The University of Essex (UK) is currently advertising a Postdoctoral Research Fellow post in the Institute for Analytics and Data Science (IADS) to support the Institute?s work in analytics, data science and big data. The post is for an initial 3-year period within IADS during which the post-holder will be on probation. On successful completion of the Fellowship and the probation period, the post-holder will be offered a permanent appointment as a Lecturer in the School of Computer Science and Electronic Engineering at the University of Essex. The duties of the Postdoctoral Research Fellow include undertaking high quality independent and collaborative research that meets REF standards, applying for grants, contributing to public engagement and impact, developing interdisciplinary collaborations within IADS, supporting the research culture of the Institute, supervising students, and supporting IADS administratively. The Fellow will also undertake a limited amount of teaching to enable them to meet the requirements of probation, and to provide a good foundation in higher education practice for the Fellow's ongoing career. The person appointed will work closely with the Director of the Institute and UNESCO Chair in Analytics and Data Science, Prof Maria Fasli and Assistant Director Dr Spyros Samothrakis. Applicants should hold a PhD in Computer Science or related area and have excellent knowledge of computer science, artificial intelligence, machine learning or advanced text analytics. Particular research areas of interest include but are not limited to: - machine learning; - reinforcement learning, neural networks, deep learning; - data mining; - predictive analytics; - natural language processing and advanced text analytics; - semantic information extraction and the Semantic Web; - social media analysis; - handling of data in motion (multi-stream processing and reasoning, complex event processing and reasoning); - decision support tools and systems. For more information and to make an application, please see here: https://vacancies.essex.ac.uk/tlive_webrecruitment/wrd/run/ETREC107GF.open?VACANCY_ID%3d333171EkCU%1BUSESSION=DCC131C22B8346FFB7FC55A2DC3B41FD&WVID=9918109NEm&LANG=USA The job specification can be found here: https://www1.essex.ac.uk/hr-jobpacks/science_health-csee/REQ00948_Jobpack_Published.pdf Informal enquiries can be directed to Prof Maria Fasli (mfasli at essex.ac.uk). Professor Maria Fasli PhD, NTF, FHEA UNESCO Chair in Analytics and Data Science Director, Institute for Analytics and Data Science University of Essex T +44 (0)1206 872327 E mfasli at essex.ac.uk Follow us on Twitter @EssexIADS PA Shaaba Lotun T +44 (0)1206 873496 E slotun at essex.ac.uk ? http://www.essex.ac.uk/iads/ WE ARE ESSEX TOP 20 FOR RESEARCH EXCELLENCE -------------- next part -------------- An HTML attachment was scrubbed... URL: From m.gomez.rodriguez at gmail.com Sat Nov 25 11:03:42 2017 From: m.gomez.rodriguez at gmail.com (Manuel Gomez Rodriguez) Date: Sat, 25 Nov 2017 17:03:42 +0100 Subject: Connectionists: Faculty positions at MPI-SWS Message-ID: If you are attending NIPS and would like to know more about the positions below, please contact Manuel Gomez Rodriguez (manuelgr at mpi-sws.org) and/or Adish Singla (adishs at mpi-sws.org). ====== Applications are invited for faculty positions at all career stages in computer science, with a particular emphasis on systems (broadly construed). We expect multiple positions to be filled in systems, but exceptional candidates in other areas of computer science are also strongly encouraged to apply. A doctoral degree in computer science or related areas and an outstanding research record (commensurate for the applicant?s career stage) are required. Successful candidates are expected to build a team and pursue a highly visible research agenda, both independently and in collaboration with other groups. MPI-SWS is part of a network of over 80 Max Planck Institutes, Germany?s premier basic-research organisations. MPIs have an established record of world-class, foundational research in the sciences, technology, and the humanities. The institute offers a unique environment that combines the best aspects of a university department and a research laboratory: Faculty enjoy full academic freedom, lead a team of doctoral students and post-docs, and have the opportunity to teach university courses; at the same time, they enjoy ongoing institutional funding in addition to third-party funds, a technical infrastructure unrivaled for an academic institution, as well as internationally competitive compensation. The institute is located in the German cities of Saarbruecken and Kaiserslautern, in the tri-border area of Germany, France, and Luxembourg. We maintain an international and diverse work environment and seek applications from outstanding researchers worldwide. The working language is English; knowledge of the German language is not required for a successful career at the institute. Qualified candidates should apply on our application website ( apply.mpi-sws.org). To receive full consideration, applications should be received by December 1st, 2017. The institute is committed to increasing the representation of minorities, women, and individuals with physical disabilities. We particularly encourage such individuals to apply. The initial tenure-track appointment is for five years; it can be extended to seven years based on a midterm evaluation in the fourth year. A permanent contract can be awarded upon a successful tenure evaluation in the sixth year. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Joni.Dambre at UGent.be Mon Nov 27 05:38:04 2017 From: Joni.Dambre at UGent.be (Joni Dambre) Date: Mon, 27 Nov 2017 11:38:04 +0100 Subject: Connectionists: Vacancy: PhD or Postdoc position - Designing general-purpose analog computing based on machine learning Message-ID: <23F89325-6337-4496-A76C-637AF8094EE6@UGent.be> Imec-IDLab-UGent IDLab is a research group of UGent, as well as a core research group of imec. IDLab performs fundamental and applied research on data science and internet technology, and counts over 300 researchers. Our major research areas are machine learning and data mining; semantic intelligence; multimedia processing; distributed intelligence for IoT; cloud and big data infrastructures; wireless and fixed networking; electromagnetics, RF and high-speed circuits and systems. In particular, the group has been studying various kinds of neural networks for more than 20 years. It has been at the forefront of deep learning research ever since it became popular a decade ago. Illustrative of this success are an excellent track record at Kaggle competitions and the fact that four of our former PhD students are now working at Google?s Deepmind and one at Google Brain. The job In the context of the European H2020 project PHRESCO, we offer a PhD or postdoc position at the intersection of machine learning, photonics and dynamical systems theory. The PHRESCO research project involves the design of integrated photonic analog computers based on a machine learning technique called Reservoir Computing. For this technique, a physical nonlinear dynamical system (the reservoir) is considered to be computing a number of functions of its past and present inputs in its state variables. To perform useful computation with such a system, these functions can be linearly combined to approximate a desired input/output behavior. The overall nature of the state functions is generally affected by some global parameters which can be tuned to best accommodate the desired functionality. The resulting modules offer tunable general-purpose analog computing, but they can not be scaled up to solve complex tasks. In order to go further with this, the next step is to develop a systematic design methodology that allows to automatically extract/design a multi-reservoir system from a task description that is specified by examples, like in a typical machine learning flow. Although the project addresses photonic implementations, the design methodology should be suitable for any analog implementation medium. This research is situated at the intersection of machine learning, analog hardware design, nonlinear dynamical systems and should also build upon the vast experience that exists related to system design (e.g., in the digital community). Profile: We are looking for an excellent PhD student or postdoc with a keen interest in exploring alternatives to traditional digital computation. Candidates should ideally have experience with machine learning. A background in hardware design or the development of a hardware design methodology is an asset. A background in photonics is not necessary, but some knowledge is helpful. Also, candidates should be very creative in combining ideas from different domains. We offer an exciting job in a stimulating environment, with a nice amount of flexibility and academic liberty. Your research will be supported by our own research group, with a thorough expertise in machine learning and (photonic) reservoir computing, as well as the photonics research group in the INTEC department (group of prof. P. Bienstman, also at Ghent University - imec), which mainly addresses the technological implementation of such systems. Requirements: Applicants should have a Masters degree (for a PhD position) or PhD (for a postdoc position), preferably in computer science or electronics engineering or computational/cognitive neuroscience. Note: to be admissible to the PhD-program, your degree must be equivalent to 5 years of engineering studies (bachelor + master) in the European Union. You have an excellent academic track record (graduation cum laude or grades in the top 25% percentile). You have a background in machine learning. You can illustrate you interdisciplinary mindset by previous interdisciplinary projects or by combining a background in as many as possible of the following fields: neural networks, analog or digital hardware design methodology, optimization theory, computational or cognitive neuroscience, signal processing, nonlinear control theory, compressed sensing, stochastic processes, applied physics, photonic/optical computing. You are interested in and motivated by the research topic, as well as in obtaining a PhD degree. You have excellent analytical skills. You are a native Dutch speaker or speak and write English fluently (C1 CEFR level). You have good communication skills. You are eligible for a Flemish PhD scholarship (i.e., you have not enjoyed such a scholarship before). You are preferably available from January 1st or shortly after. Our offer: We offer a fully funded PhD scholarship for a maximal period of 4 years (upon positive progress evaluation). The PhD research is fundamental and innovative, but with clear practical applications. You will join a young and enthusiastic team of researchers, post-docs and professors. This PhD position is available from January 1st, 2018. Interested? Apply with extensive motivation letter, scientific resume, diplomas and detailed academic results (courses and grades), English proficiency scores (for non Dutch speakers), relevant publications, and two reference contacts. For any questions, contact prof. dr. ir. Joni Dambre . After the first screening, suitable candidates will be invited for an interview (also possible via Skype) and may get an assignment for skills assessment. prof. dr. ir. Joni Dambre, IDLab, Ghent University - imec Electronics and Information Systems Department, Engineering Faculty iGent building, Technologiepark 15, 9052 Zwijnaarde, Belgium work phone: +32-9-264.34.09 email: Joni.Dambre at UGent.be -------------- next part -------------- An HTML attachment was scrubbed... URL: From Joni.Dambre at UGent.be Mon Nov 27 05:43:38 2017 From: Joni.Dambre at UGent.be (Joni Dambre) Date: Mon, 27 Nov 2017 11:43:38 +0100 Subject: Connectionists: =?utf-8?q?Vacancy=3A_PhD_position_=E2=80=93_Power?= =?utf-8?q?-scalable_embedded_vision_sensors?= Message-ID: Imec-IDLab-UGent IDLab is a research group of UGent, as well as a core research group of imec. IDLab performs fundamental and applied research on data science and internet technology, and counts over 300 researchers. Our major research areas are machine learning and data mining; semantic intelligence; multimedia processing; distributed intelligence for IoT; cloud and big data infrastructures; wireless and fixed networking; electromagnetics, RF and high-speed circuits and systems. In particular, the group has been studying various kinds of neural networks for more than 20 years. It has been at the forefront of deep learning research ever since it became popular a decade ago. Illustrative of this success are an excellent track record at Kaggle competitions and the fact that four of our former PhD students are now working at Google?s Deepmind and one at Google Brain. The job Within the context of the recently approved FWO project HYPERSCALES, conducted at UGent IDLab (http://www.ugent.be/ea/idlab/) and at KULeuven, we are looking for an excellent PhD student to work on power efficient embedded sensing solutions by developing hardware-aware deep learning architectures. You will collaborate with enthusiastic colleagues at IDLab, as well as with our partners atKULeuven, who will focus on the hardware design. You will research and develop suitable hardware-efficient architectures and training approaches and stay up to date with important changes in the related literature. You will be encouraged to publish and present your work at international conferences, or to attend useful summer schools. Requirements: You have a degree in Master of Science/Engineering, preferably in Computer Science, Electronics-ICT or (Mathematical) Informatics. Note: to be admissible to the PhD-program, your degree must be equivalent to 5 years of engineering studies (bachelor + master) in the European Union, and you must have a solid academic track record (graduation cum laude or grades in the top 25% percentile). You have a strong interest in the above-mentioned domains. You are interested in and motivated by the research topic, as well as in obtaining a PhD degree. You have excellent analytical skills. You are a native Dutch speaker or speak and write English fluently (C1 CEFR level). You have good communication skills. You have an open mind and a multi-disciplinary attitude. You have knowledge of and experience with machine learning. Having prior experience with deep learning is an asset. You are eligible for a Flemish PhD scholarship (i.e., you have not enjoyed such a scholarship before). You are preferably available from January 1st or shortly after. Our offer: We offer a fully funded PhD scholarship for a maximal period of 4 years (upon positive progress evaluation). The PhD research is fundamental and innovative, but with clear practical applications. You will join a young and enthusiastic team of researchers, post-docs and professors. This PhD position is available from January 1st, 2018. Interested? Apply with motivation letter, scientific resume, diplomas and detailed academic results (courses and grades), English proficiency scores (for non Dutch speakers), relevant publications, and two reference contacts. For any questions, contact prof. dr. ir. Joni Dambre . After the first screening, suitable candidates will be invited for an interview (also possible via Skype) and may get a machine learning assignment. prof. dr. ir. Joni Dambre, IDLab, Ghent University - imec Electronics and Information Systems Department, Engineering Faculty iGent building, Technologiepark 15, 9052 Zwijnaarde, Belgium work phone: +32-9-264.34.09 email: Joni.Dambre at UGent.be -------------- next part -------------- An HTML attachment was scrubbed... URL: From zfalomir at gmail.com Mon Nov 27 10:49:15 2017 From: zfalomir at gmail.com (Zoe Falomir) Date: Mon, 27 Nov 2017 16:49:15 +0100 Subject: Connectionists: SI ProSocrates, Cognitive Systems Research (Deadline Extended: 15 Dec) Message-ID: Special Issue on Problem-solving, Creativity and Spatial Reasoning in Cognitive Systems (ProSocrates) @ Cognitive Systems Research, Elsevier The focus of this ProSocrates Special Issue is to bring problem-solving, spatial cognition/reasoning, cognitive systems and creativity disciplines together, by bringing in dialogue specialists from each of the fields. Authors of experimental, theoretical and computational work which combines perspectives from at least 2 these topics are invited to submit contributions. The larger aim of integrating these topics is to produce theoretical tools, approaches and methodologies for creative and spatial problem solving in cognitive systems, in a manner that would benefit from such interdisciplinary bootstrapping. Papers included in this issue will address such questions/debates as: How spatial reasoning can help in problem solving? How can problems be modeled in order to be solved creatively? How can spatial reasoning improve cognitive and/or creative skills in people? and in cognitive systems? What is the relation between Creativity and Spatial Reasoning? How sketches, shapes and colours can be interpreted cognitively and/or creatively? What is the relation between computational creativity, cognitive creativity and reasoning? How analogy and metaphor, image schemas and concept blending shed light on creative problem solving? Possible topics to be explored by the contributions to this special issue include: Spatial cognition, creative cognition Spatial reasoning, case-based reasoning, analogical reasoning General and spatial problem solving, knowledge representation for problem-solving, cross-modal creativity and problem solving Analogy and metaphor, concept blending, image schemas Cognitive modeling and qualitative modeling Computational creativity, computational cognitive systems Symbolic, subsymbolic and hybrid approaches, evolutionary approaches and genetic algorithms Systems for enhancing human spatial reasoning and/or creativity Cognitive recommender systems, natural and artificial cognitive systems Visuospatial creativity, insight and re-representation Applications in Education, Robotics, Design, etc. SUBMISSION GUIDELINES Submissions to the special issue must include original research. Papers must be new and have not been published or submitted to other journals. Authors should prepare their manuscript according to the "Guide for Authors" available at the journal homepage: http://www.journals.elsevier.com/cognitive-systems-research/. Submission should be made via the EVISE system: https://www.evise.com/profile/api/navigate/COGSYS Authors must select ?VSI: ProSocrates? when they reach the "Article Type" step in the submission process. All papers will be peer-reviewed following the reviewing procedures of the Cognitive Systems Research (CSR) journal. All papers will undergo a preliminary screening to ensure relevance to the special issue prior to be the peer-review phase; research papers that do not sufficiently address the special issue call may not be selected for a full peer review (such a decision will be communicated rapidly). IMPORTANT DATES Deadline for paper submission (Extended): December 15th, 2017 Notification of acceptance: July 15th, 2018 Publication date: September 15th, 2018 GUEST EDITORS Zoe Falomir University of Bremen, Bremen Spatial Cognition Centre, Germany zfalomir at uni-bremen.de http://cosy.informatik.uni-bremen.de/staff/zoe-falomir-llansola Ana-Maria Olte?eanu University of Bremen, Bremen Spatial Cognition Centre, Germany amoodu at informatik.uni-bremen.de http://cosy.informatik.uni-bremen.de/staff/ana-maria-olteteanu -- ------------------------------------------------------------ Dr.-Ing. Zoe Falomir Llansola https://sites.google.com/site/zfalomir/home Twitter at @zfalomir ------------------------------------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From Izhar.Bar-Gad at biu.ac.il Tue Nov 28 03:01:13 2017 From: Izhar.Bar-Gad at biu.ac.il (Izhar Bar-gad) Date: Tue, 28 Nov 2017 08:01:13 +0000 Subject: Connectionists: Faculty positions at Bar Ilan University Message-ID: The Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center at Bar-Ilan University anticipates new tenure track positions (rank commensurate with qualifications and experience), starting in the academic years 2018-2019. We are looking for excellent early-stage scientists who aspire to establish innovative and interdisciplinary research programs in neuroscience or related fields essential for understanding the brain. While all applicants will be evaluated for merit, we are particularly interested to recruit scientists with expertise in theoretical and computational neuroscience. The appointments are subject to budgetary approval. The Gonda Brain Research Center at Bar-Ilan University brings together researchers in a variety of fields essential for understanding the brain, including biology, psychology, linguistics, computing and physics. Research at the Gonda Center studies the brain at all levels - from behavior and cognitive processing through neural circuits, all the way to molecular mechanisms, in health and in disease. Candidates are expected to have a PhD (or equivalent) and post-doctoral training in relevant fields, and to show excellent track-record for their stage of career. Interested candidates should first submit a letter of application and a curriculum vita. For more information enquiries and applications please contact Tami Rubenov (tami.rubenov at biu.ac.il). BIU is an equal opportunity employer and all qualified applicants will receive consideration for employment. Please forward this message to anyone who might be interested. Izhar Bar-Gad Associate Professor Gonda Brain Research Center Bar Ilan University Ramat-Gan 52900, Israel Phone: +972-3-531-7141 Cell: +972-54-998-4206 Fax: +972-3-535-2184 Email: izhar.bar-gad at biu.ac.il WWW: http://www.ibglab.org/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From veronica.bolon at udc.es Tue Nov 28 07:44:56 2017 From: veronica.bolon at udc.es (=?utf-8?Q?Ver=C3=B3nica_Bol=C3=B3n?=) Date: Tue, 28 Nov 2017 13:44:56 +0100 Subject: Connectionists: CFP for IJCNN18 Special Session on Parallelism on Machine Learning: Theory and Applications Message-ID: <3CA6DE93-1142-4D4E-A798-52608AB2F880@udc.es> [Apologies if you receive multiple copies of this CFP] Call for papers: special session on ?Parallelism in Machine Learning: Theory and Applications? at IJCNN 2018 International Joint Conference on Neural Networks, hosted at IEEE World Congress on Computational Intelligence (IEEE WCCI 2018) 8-13 July 2018, Rio de Janeiro, Brazil - http://www.ecomp.poli.br/~wcci2018/ Parallelism in Machine Learning: Theory and Applications Organized by: Veronica Bolon-Canedo, Jorge Gonzalez-Dominguez, Amparo Alonso-Betanzos (University of A Coru?a, Spain), Beatriz Remeseiro (University of Oviedo, Spain) Machine learning (ML) is a prolific research area focused on the study and definition of algorithms able to learn from and make predictions on data. The current technologies and the use of Internet have revolutionized the way in which people acquire, store, or share data, resulting in huge amounts of information. In order to deal with massive volumes of data, ML techniques have to learn complex models with millions of parameters, increasing the computational cost involved. Parallel programming and distributed learning are gaining attention in the last years as a mean to alleviate the effects of this extremely increase of computational cost. The efficient exploitation of High Performance Computing (HPC) resources such as multicore CPUs, hardware accelerators (GPUs, Intel Xeon Phi coprocessors, FPGAs, etc.), clusters or cloud-based systems can significantly accelerate many ML algorithms. This increase of speed allows ML users to either reduce the time needed for their applications or to search a larger space in the same period of time. We invite papers on both practical and theoretical issues about incorporating parallel and distributed approaches into machine learning problems. In particular, topics of interest include, but are not limited to: Development of parallel machine learning algorithms on multicore and manycore architectures: multithreading, GPUs, Intel Xeon Phi coprocessor, FPGAs, etc. Development of distributed machine learning algorithms. Exploitation of cloud, grid and distributed-memory systems to accelerate machine learning algorithms: Spark, Hadoop, MPI, etc. Scalability analysis of parallel and distributed methods for machine learning. Performance comparison of parallel and distributed machine learning algorithms. Deep learning models trained across multicore CPUs, GPUs or clusters of computers. Applications: bioinformatics, medicine, multimedia, marketing, cyber security, etc. Submitted papers will be reviewed according to the IJCNN reviewing process and will be evaluated on their scientific value: originality, correctness, and writing style. IMPORTANT DATES: Paper submission: 15th January 2018 Paper acceptance: 15th March 2018 Final paper submission: 1st May 2018 Early registration: 1st May 2018 IEEE WCCI 2018 conference: 8-13 July 2018 Ver?nica Bol?n Canedo, PhD Grupo LIDIA Departamento de Computaci?n Facultad de Inform?tica Universidade da Coru?a Campus de Elvi?a, s/n 15071 - A Coru?a, Spain Phone: +34 981 167150 Ext. 6007 Fax: +34 981 167160 e-mail: veronica.bolon at udc.es http://www.lidiagroup.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephan.busemann at dfki.de Tue Nov 28 10:00:38 2017 From: stephan.busemann at dfki.de (Stephan Busemann) Date: Tue, 28 Nov 2017 16:00:38 +0100 Subject: Connectionists: Researcher in Machine Learning for NLP with a Focus on Deep Learning and, Machine Translation, DFKI, Germany Message-ID: <69242729-b2e7-6f6d-9fff-33ffa073097b@dfki.de> [Apologies for crossposting]* Researcher in Machine Learning for NLP with a Focus on Deep Learning and ** **Machine Translation, DFKI, Germany * The Multilingual Technologies (MLT) Lab at DFKI is looking to expand its expertise in Machine Learning for NLP with a focus on Deep Learning and Machine Translation. Depending on track record and experience, the position is available at the Junior/Researcher/Senior level. *Research responsibilities include: * - machine learning and deep learning for machine translation - publication in top-tier conferences and journals - software development and integration /General responsibilities include:/ - basic research as well as industry funded applied research - identification of funding opportunities and engagement in proposal writing - contribution to teaching and supervision in accordance with University and ? DFKI rules and regulations - administrative work associated with programmes of research /Requirements: / - MSc/PhD in computer science, machine learning, natural language processing, ? computational linguistics or similar - Strong background and track record in machine learning and deep learning as ? well as in MT and NLP - Strong problem solving and programming skills, independent and creative ? thinking - Strong team working and communication skills, as well as excellent command ? of written and oral English. Command of German or other languages will be? helpful, but is not a requirement. Successful applicants will work in the DFKI MLT lab led by Prof. Josef van Genabith (Scientific Director MLT, DFKI, and Chair of Translation-Oriented Language Technologies, Saarland University). /Starting date, duration, salary: / Preferred starting dates are early Spring 2018.? The position is available for a duration of three years, with opportunities for extension depending on performance and future funding. Compensation is competitive and reflects individual competence, seniority and special skills. /Application: / Applications are required to include a short cover letter, a CV, list of publications, a brief summary of research interests, and contact information for three references. Please send your electronic application (preferably in PDF format) and inquiries to mlt-sek at dfki.de referring to job opening no. 97/17/JvG. Deadline for applications is November 30th, 2017. The position remains open until filled. Please contact josef.van_genabith at dfki.de for informal inquiries. -- Prof.Dr. Stephan Busemann, Principal Researcher Associate Head of Language Technology Department DFKI GmbH, Stuhlsatzenhausweg 3, D-66123 Saarbruecken phone: (+49 681) 85775-5286, fax: (+49 681) 85775-5338 http://www.dfki.de/~busemann ------------------------------------------------------------- Deutsches Forschungszentrum fuer Kuenstliche Intelligenz GmbH Trippstadter Strasse 122, D-67663 Kaiserslautern, Germany Geschaeftsfuehrung: Prof. Dr. Dr. h.c. mult. Wolfgang Wahlster (Vorsitzender) Dr. Walter Olthoff Vorsitzender des Aufsichtsrats: Prof. Dr. h.c. Hans A. Aukes Amtsgericht Kaiserslautern, HRB 2313 ------------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From erdi.peter at wigner.mta.hu Tue Nov 28 13:59:04 2017 From: erdi.peter at wigner.mta.hu (=?ISO-8859-2?Q?=C9rdi_P=E9ter?=) Date: Tue, 28 Nov 2017 19:59:04 +0100 (CET) Subject: Connectionists: Cognitive Systems Research: Volume 47, Pages 1-226, January 2018 Message-ID: The foundations of socionics - A review Karol Pietrak Pages 1-11 Dynamics properties of knowledge acquisition Sergey Petrov Pages 12-15 Question classification in Persian using word vectors and frequencies Mohammad Razzaghnoori, Hedieh Sajedi, Iman Khani Jazani Pages 16-27 Identifying influential segments from word co-occurrence networks using AHP Muskan Garg, Mukesh Kumar Pages 28-41 Learning ?ukasiewicz logic Frederik Harder, Tarek R. Besold Pages 42-67 Unsupervised construction of human body models Thomas Walther, Rolf P. W?rtz Pages 68-84 Dynamics of the knowledge instinct: Effects of incoherence on the cognitive system F?lix Schoeller, Micka?l Eskinazi, Damien Garreau Pages 85-91 Towards reasoning based representations: Deep Consistence Seeking Machine A. L?rincz, M. Cs?kv?ri, ?. F?thi, Z.?. Milacski, A. S?rk?ny, Z. T?s?r Pages 92-108 Representing decision-makers using styles of behavior: An approach designed for group decision support systems Joao Carneiro, Pedro Saraiva, Diogo Martinho, Goreti Marreiros, Paulo Novais Pages 109-132 With a little help from my friends: A computational model for the role of social support in mood regulation Seyed Amin Tabatabaei, Altaf Hussain Abro, Michel Klein Pages 133-146 A computational cognitive framework of spatial memory in brains and robots Tamas Madl, Stan Franklin, Ke Chen, Robert Trappl Pages 147-172 Applying matrix factorization techniques to compare experts' categorization process during case formulation task performed by concept maps Piotr Kaczmarek, Anna S?ysz Pages 173-185 Conscious agent networks: Formal analysis and application to cognition Chris Fields, Donald D. Hoffman, Chetan Prakash, Manish Singh Pages 186-213 Emotion-based Hangul font recommendation system using crowdsourcing Hyun-Young Kim, Soon-Bum Lim Pages 214-225 ************ P?ter ?rdi Editor-in-Chief "Follow me" at aboutranking.com ! From nicosia at dmi.unict.it Tue Nov 28 11:19:46 2017 From: nicosia at dmi.unict.it (Giuseppe Nicosia) Date: Tue, 28 Nov 2017 16:19:46 +0000 Subject: Connectionists: ACDL 2018, Advanced Course on Data Science and Machine Learning - Early Registration March 31 Message-ID: ACDL 2018, Advanced Course on Data Science and Machine Learning - Early Registration March 31 Advanced Course on Data Science and Machine Learning An Interdisciplinary Course: Data Science, Machine Learning and Artificial intelligence without Borders ACDL 2018 ? A Unique Experience: Data Science & Machine Learning with the World?s Leaders in the fascinating atmosphere of the ancient Certosa di Pontignano Certosa di Pontignano, Siena - Tuscany, Italy July 19-23, 2018 https://acdl2018.icas.xyz/ Early registration deadline: March 31, 2018 https://acdl2018.icas.xyz/registration/ LECTURERS: Roman Belavkin, Middlesex University London, UK Yoshua Bengio, University of Montreal, Canada Sergiy Butenko, Texas A&M University, USA Yi-Ke Guo, Imperial College London, UK Yann LeCun, Director of AI Research, Facebook New York University, USA Peter Norvig, Director of Research, Google Panos Pardalos, University of Florida, USA Alex 'Sandy' Pentland, MIT, USA Mauricio Resende, Amazon, USA More speakers to be announced soon! SCOPE: The Advanced Course is not a summer school suited only for younger scholars. Rather, a significant proportion of seasoned investigators are regularly present among the attendees, often senior faculty at their own institutions. The balanced audience that we strive to maintain in each Advanced Course greatly contributes to the development of intense cross-disciplinary debates among faculty and participants that typically address the most advanced and emerging areas of each topic. Each faculty member presents lectures and discusses with the participants for one entire day. Such long interaction together with the small, exclusive Course size provides the uncommon opportunity to fully explore the expertise of each faculty, often through one-to-one mentoring. This is unparalleled and priceless. The Certosa di Pontignano provides the perfect setting to a relaxed yet intense learning atmosphere, with the stunning backdrop of the Tuscan landscapes. World-class wines and traditional foods will make the Advanced Course on Data Science and Machine Learning the experience of a lifetime. VENUE & ACCOMMODATION: The venue of ACDL 2018 will be The Certosa di Pontignano ? Siena The Certosa di Pontigniano Loc. Pontignano, 5 ? 53019, Castelnuovo Berardenga (SI) ? Tuscany ? Italy phone: +39-0577-1521104 fax: +39-0577-1521098 info at lacertosadipontignano.com http://www.lacertosadipontignano.com/ A few kilometres from Siena, on a hill dominating the town stands the ancient Certosa di Pontignano, a unique place where nature, history and hospitality blend together in memorable harmony. Built in the 1300, its medieval structure remains intact with additions of the following centuries. The Certosa is centred on its historic cloisters and gardens. https://acdl2018.icas.xyz/venue/ REGISTRATION: https://acdl2018.icas.xyz/registration/ CERTIFICATE: Participants will be delivered a certificate of attendance indicating the number of hours of lectures. lod at icas.xyz https://acdl2018.icas.xyz/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From nian.zhang6 at gmail.com Wed Nov 29 11:12:41 2017 From: nian.zhang6 at gmail.com (Nian Ashlee Zhang) Date: Wed, 29 Nov 2017 11:12:41 -0500 Subject: Connectionists: Call for Abstract - 2018 ASEE Mid-Atlantic Spring Conference, UDC, Washington, D.C., April 6-7, 2018 Message-ID: *Welcome to 2018 ASEE Mid-Atlantic Spring Conference* *at UDC!* *Washington, D.C., April 6-7, 2018* UDC Student Center University of the District of Columbia Washington, D.C., April 6-7, 2018 https://sites.google.com/view/asee-spring2018-udc *"Educating the Engineers and Scientists of the 21st Century"* The American Society for Engineering Education (ASEE) is a premier association dedicated to promoting and improving engineering and engineering technology education. The Mid-Atlantic Section covers a broad geographic area, including New York City area, New Jersey, Delaware, Maryland and Washington, DC to mid-State Pennsylvania. The School of Engineering and Applied Sciences (SEAS) at University of the District of Columbia (UDC) is pleased to invite Engineering and Engineering Technology educators, students and representatives of industry and government interested in engineering education to the 2018-ASEE Mid Atlantic Spring Conference, during April 6-7, 2018, at the University of the District of Columbia. The University of the District of Columbia is the only urban land-grant institution of higher education and the only public university in the nation?s capital. UDC is committed to provide affordable access to high-quality post-secondary education, research and community service. Our vision is to be a diverse, selective, teaching, research and service university in the land-grant tradition, serving the people of Washington, DC, the nation and the world. Established by abolitionist Myrtilla Miner in 1851, the University of DC offers Associate's, Bachelor's and Master's Degrees and a host of workplace development services designed to create opportunities for students? success. The University is comprised of a Community College , School of Engineering and Applied Sciences , School of Business and Public Administration , College of Arts and Sciences , College of Agriculture, Urban Sustainability and Environmental Sciences , and the David A. Clarke School of Law . The ASEE Mid-Atlantic Conference ( http://www.asee.org/conferences-and-events/meetings/section-meetings ) is dedicated to all disciplines of engineering education. The main focus will be on fostering the exchange of ideas, enhancing teaching methods and curriculum, and providing networking opportunities for engineering, engineering technology educators, students and industry, government representatives interested in engineering education. The conference will feature plenary speeches and regular sessions with broad coverage, and special sessions focusing on popular topics. An award will be given to the best paper. We invite papers on all topics of interest to engineering educators, including but not limited to: - Multi-Disciplinary Engineering - Entrepreneurship Education/Mentoring - Online-Learning - Innovations in Teaching Engineering - Service and Project-Based Learning - Senior Capstone Design Projects - Undergraduate and graduate Research Projects - Research Experience for Undergraduates (REU) - Improving Critical Thinking - Increasing Diversity in Engineering - Ethics in Engineering Education - K-16 Engineering Education - Teacher Empowerment in Engineering Education - Balancing Teaching and Research - Getting More Women into Engineering and Computer Science - Practicing Experiential Learning - Innovative Teaching - Grand Challenges *Submission Timeline* 250-word Abstract Submission: January 15, 2018 Decision Notification: February 15, 2018 Final Full Paper Submission: March 15, 2018 Deadline for Author Registration: March 15, 2018 *Publication* All final accepted papers will be archived and distributed to all conference attendees. A search engine of all the papers presented will be available on ASEE website. In order for a paper to be included in the ASEE archive, the author of a submitted paper must agree to have the paper distributed (this is not a copyright release, only an agreement to distribute). Either the main author or one of the co-authors must be registered for the conference by March 15, 2018. All documents must be submitted online in PDF format via the conference website. Templates are provided on the submission guidelines page. *Presentation* In order to schedule a presentation slot, at least one author (preferably the presenting author) from each accepted paper/abstract/poster must register for the conference no later than March 15, 2018, which is the Author Registration deadline. If no author for an accepted paper has registered by March 15, 2018, the paper will be removed from the conference. *Author Responsibilities* Any person may submit to this conference, whether or not he/she is an ASEE member. The author who submits the abstract, paper or poster is responsible for adhering to all deadlines. Abstract/paper/poster information can only be edited and updated by the person who submits it. *Organizing Committee* Dr. Devdas Shetty *Honorary Chair* Dean of School of Engineering and Applied Sciences (SEAS) Professor of the Department of Mechanical Engineering Dr. Nian Zhang *Chair* Associate Professor of the Department of Electrical and Computer Engineering Dr. Paul Cotae *Vice Chair* Professor of the Department of Electrical and Computer Engineering Dr. Ahmet Zeytinci *ASEE Middle Atlantic Section Chair-Elect 2017-2018* Professor of the Department of Civil Engineering -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Call for Papers and Posters.pdf Type: application/pdf Size: 245783 bytes Desc: not available URL: From dwang at cse.ohio-state.edu Wed Nov 29 16:42:03 2017 From: dwang at cse.ohio-state.edu (WANG, DELIANG) Date: Wed, 29 Nov 2017 16:42:03 -0500 Subject: Connectionists: NEURAL NETWORKS, Dec. 2017 Message-ID: Neural Networks - Volume 96, December 2017 http://www.journals.elsevier.com/neural-networks Fixed-time synchronization of memristor-based BAM neural networks with time-varying discrete delay Chuan Chen, Lixiang Li, Haipeng Peng, Yixian Yang ASD+M: Automatic parameter tuning in stochastic optimization and on-line learning Pawe? Wawrzynski User emotion for modeling retweeting behaviors Jinpeng Chen, Yu Liu, Ming Zou Robust spike-train learning in spike-event based weight update Sumit Bam Shrestha, Qing Song Robust Alternating Low-Rank Representation by joint image- and image-norm minimization Zhao Zhang, Mingbo Zhao, Fanzhang Li, Li Zhang, Shuicheng Yan Post-boosting of classification boundary for imbalanced data using geometric mean Jie Du, Chi-Man Vong, Chi-Man Pun, Pak-Kin Wong, Weng-Fai Ip Lifelong learning of human actions with deep neural network self-organization German I. Parisi, Jun Tani, Cornelius Weber, Stefan Wermter Mittag-Leffler synchronization of fractional neural networks with time-varying delays and reaction?diffusion terms using impulsive and linear controllers Ivanka Stamova, Gani Stamov Global exponential stability of nonautonomous neural network models with unbounded delays Jose J. Oliveira Some new results on stability and synchronization for delayed inertial neural networks based on non-reduced order method Xuanying Li, Xiaotong Li, Cheng Hu Synchronization stability of memristor-based complex-valued neural networks with time delays Dan Liu, Song Zhu, Er Ye A new approach to optimal control of conductance-based spiking neurons Xuyang Lou, M.N.S. Swamy Robust artificial neural network for reliability and sensitivity analyses of complex non-linear systems Uchenna Oparaji, Rong-Jiun Sheu, Mark Bankhead, Jonathan Austin, Edoardo Patelli From tom_griffiths at berkeley.edu Thu Nov 30 00:16:26 2017 From: tom_griffiths at berkeley.edu (Tom Griffiths) Date: Wed, 29 Nov 2017 21:16:26 -0800 Subject: Connectionists: Postdoctoral position in computational cognitive science Message-ID: <15C29558-2695-475F-B351-A40348CF1D4C@berkeley.edu> My lab is moving to Princeton University in July 2018, and we will have postdoctoral positions available in computational cognitive science. Applicants should have a background in cognitive science or a related discipline such as computer science or psychology, with a research agenda focused on using mathematical, computational, and behavioral methods to understand the nature of human intelligence. Current research in the lab explores a wide range of topics including more realistic models of rational behavior (bounded optimality and rational metareasoning, with applications to decision-making and strategic behavior), novel methods for using behavioral data to answer questions about the mind (crowdsourcing, analysis of large online datasets, automated design and optimization of experiments), and the interface of human and machine learning (comparing deep learning to human behavior, Bayesian machine learning, metalearning, hierarchical reinforcement learning). Further details and application materials are available here (deadline December 17): https://puwebp.princeton.edu/AcadHire/apply/application.xhtml?listingId=5082 (This listing is in the Department of Computer Science but appointments can also be made in Psychology if preferred, just note this in your application.) I will be at NIPS if you would like to discuss the position. Best wishes, Tom. -- Tom Griffiths Professor, Psychology and Cognitive Science University of California, Berkeley http://cocosci.berkeley.edu/tom/ From terry at salk.edu Wed Nov 29 20:59:22 2017 From: terry at salk.edu (Terry Sejnowski) Date: Wed, 29 Nov 2017 17:59:22 -0800 Subject: Connectionists: NEURAL COMPUTATION - December 1, 2017 In-Reply-To: Message-ID: Neural Computation - Volume 29, Number 12 - December 1, 2017 Available online for download now: http://www.mitpressjournals.org/toc/neco/29/12 ----- Articles Noise-Robust Modes of the Retinal Population Code Have the Geometry of "Ridges" and Correspond With Neuronal Communities Adrianna Renee Loback, Jason S Prentice, Mark L Ioffe, and Michael J. Berry II Delay Differential Analysis of Seizures in Multi-channel Electrocorticography Data Claudia Lainscsek, Jonathan Weyhenmeyer, Sydney S. Cash, and Terrence J Sejnowski Letters First Passage Time Memory Lifetimes for Simple, Multistate Synapses Terry Elliott Capturing the Dynamical Repertoire of Single Neurons With Generalized Linear Models Alison I Weber, Jonathan W. Pillow Neural Decoding: A Predictive Viewpoint Valerie Ventura Dopamine, Inference and Uncertainty Samuel Gershman Learning Simpler Language Models With the Differential State Framework Alexander G Ororbia II, Tomas Mikolov, and David Reitter Learning Rates for Classification With Gaussian Kernels Shaobo Lin, Jinshan Zeng, and Xiangyu Chang Refined Spectral Clustering via Embedded Label Propagation Yan-Shuo Chang, Feiping Nie, Zhihui Li, Xiaojun Chang, and Heng Huang ------------ ON-LINE -- http://www.mitpressjournals.org/neuralcomp SUBSCRIPTIONS - 2017 - VOLUME 29 - 12 ISSUES Student/Retired $80 Individual $142 Institution $1,141 MIT Press Journals, One Rogers Street, Cambridge, MA 02142-1209 Tel: (617) 253-2889 FAX: (617) 577-1545 journals-cs at mit.edu ------------ From gemmar at mit.edu Thu Nov 30 11:43:32 2017 From: gemmar at mit.edu (Gemma Roig) Date: Thu, 30 Nov 2017 16:43:32 +0000 Subject: Connectionists: JOB: RESEARCH SCIENTIST POSITIONS AT ARTIFICIAL INTELLIGENCE PROGRAMME, A*STAR, SINGAPORE Message-ID: Hello, I am sending this job post on behalf of Dr. Seng-Beng Ho from A*STAR. ?????????????????????????????????????????????????????????????????????????????????????????? To apply, send your CV to Dr. Seng-Beng Ho at hosb at ihpc.a-star.edu.sg. Who we are We are seeking exceptional researchers to expand our dynamic and multi-disciplinary AI team. Our team members have PhDs in computer science, information systems, psychology, cognitive science and neuroscience. We work on some of the most crucial, incredibly hard, and future-oriented problems in AI. We are building a nimble, team-oriented, startup-like environment with the backing and resources of A*STAR, Singapore?s national-level full-spectrum R&D organisation: https://www.a-star.edu.sg/ . We are looking for a mix of people: researchers with strong publications, but who also bring something extra to the team: Visionaries who can see beyond the current hype cycle Innovators who have ideas for creating truly intelligent systems Pathfinders who are not afraid to attempt high-risk-high-reward lines of research Tinkerers who like to open the hood of state-of-the-art models and get their hands dirty Engineers who want to design and build robust systems and scale them up for real-world problems What we work on The goal of our programme is to develop next-generation AI technologies that will enable machines to: 1) Learn like humans (as would a child from instruction, demonstration, or experience with a small number of examples); 2) Reason for humans (by being able to explain their reasoning, and to personalise recommendations based on their understanding of individual users); and, 3) Deeply understand humans (using knowledge of human needs/motivations, social/cultural norms, and commonsense). Our overarching technical approach is to combine various state-of-the art techniques with top-down knowledge. Briefly, our current research topics include: Personalised explainable AI: AI that is able to provide personalised explanations of the reasoning underlying its recommendations and decisions Socio-cultural visual intelligence: AI that can provide coherent descriptions of visual scenes taking context and social-cultural knowledge into account Socio-cultural understanding of speech and text: AI that can recognise figurative language, infer their social-cultural significance, and ultimately, understand meaning in speech and texts Human-like learning and Instructable AI: AI that can learn from real-world experience, and be programmed by non-experts, through verbal/text instruction and visual demonstrations Cognitive architectures: Cognitive architectures have the goal of bringing together the necessary cognitive machinery necessary for general artificial intelligence for autonomous behaviour. Apply to find out more (or propose your own ideas)! What you?ll receive Internationally-competitive salary and full benefits Collaboration opportunities with our network of leading international researchers Funding for international conferences and training courses Opportunities to supervise or co-supervise graduate and undergraduate students Flexibility to choose and move between basic research, applied research and commercialisation Ability to tap on the organisational infrastructure and network of a 5000-strong research organisation Experience of working and living in a vibrant, multi-cultural city at the heart of South-East Asia What you might bring to the table You should have: A Ph.D. in any AI-related area (e.g. cognitive science, computer vision, deep learning, information retrieval, knowledge representation, linguistics, machine learning, natural language processing, psychology, reasoning, robotics, etc.) Publications in top conferences and journals in your area Strong programming skills or other quantitative skills (e.g. statistical analysis) Ability to both work independently and in small teams To apply, send your CV to Dr. Seng-Beng Ho at hosb at ihpc.a-star.edu.sg. -------------- next part -------------- A non-text attachment was scrubbed... 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