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POSITION: Research Associate in the field Machine Learning and AI
(SAIL-Teilprojekt R2.1: Self-aware AI, resilience and preparedness)<br>
LOCATION: Bielefeld University of Applied Sciences, Bielefeld,
Germany<br>
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With more than 10,000 students, Bielefeld University of Applied
Sciences is the largest university of applied sciences in East
Westphalia-Lippe (OWL). Based in Bielefeld, Minden and Gütersloh, it
has an excellent network not only in the OWL region, but also
nationally and internationally through diverse contacts,
partnerships and cooperations in science, economy, politics and
culture. The Faculties of Design, Minden Campus, Engineering and
Mathematics, Social Sciences, Business and Health strive for high
quality in teaching and research.<br>
<br>
Within the framework of the funding announcement “Networks 2021”
(Netzwerke 2021) by the Ministry of Culture and Science of the State
of North Rhine-Westphalia (MKW NRW) for the sponsored project
“SustAInable Life-cycle of Intelligent Socio-Technical Systems”
(SAIL), the Faculty of Engineering and Mathematics seeks to employ a<br>
<br>
*** Research Associate in the field Machine Learning and AI (SAIL
subproject R2.1: Self-aware AI, resilience and preparedness) *** <br>
<br>
to start immediately. The **full-time position is fixed-term until
31 July 2026**. Depending on individual qualification and tasks,
remuneration will be up to salary group 13 TV-L (collective
agreement of the federal state.) A cooperative doctorate can be
pursued as part of the employment. Your workplace will be on
Bielefeld Campus.<br>
<br>
Current systems that contain AI technology are primarily targeted at
the introductory phase, a core component of which is training and
customising AI models based on given sample data. The new SAIL
research network is intended to develop the foundations for a
sustainable design of AI components. The aim is to ensure that AI
systems work transparently, safely and reliably throughout their
entire product life cycle. In addition to Bielefeld University of
Applied Sciences, this interdisciplinary network comprises Bielefeld
University, Paderborn University and OWL University of Applied
Sciences and Arts.<br>
<br>
The project addresses fundamental research in the field of AI, its
implications from the perspective of the humanities and social
sciences, as well as concrete fields of application in Industry 4.0
and Intelligent Healthcare.<br>
<br>
The predictions of AI systems are fraught with uncertainty, often
making their practical use difficult. There are several ways to
tackle this uncertainty, e.g., anticipating and correcting invalid
predictions or downstream strategies for dealing with invalid
results. In this subproject, approaches from both directions are
examined, considering both the algorithmic level and the user
perspective. In this way, AI systems could identify false
predictions in interaction with the user and improve accordingly.
The developed methods are validated using experimental setups in the
application areas “Intelligent Industrial Work Spaces” and “Adaptive
Healthcare Assistance Systems.”<br>
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Tasks and responsibilities: <br>
- Independent project coordination and implementation within the
research network<br>
- Conduct of independent research activities within the framework of
the research project:<br>
➜ Identification and definition of requirements for the AI
workflow, the algorithms to be used and the underlying
infrastructure<br>
➜ Realisation of new ML approaches based on, e.g., techniques of
active learning and modelling of uncertainty in prediction<br>
➜ Development of user interfaces for the developed AI systems<br>
➜ Generalisation and verification of the modular solution
components on Bielefeld UAS’s own research infrastructure<br>
➜ Conduct of studies with users of the newly developed systems<br>
➜ Application and transfer of research results<br>
- Instruction and guidance of student and research assistants<br>
- Knowledge transfer/publications/conference presentations<br>
- Support of project lead in other project activities within the
scope of SAIL<br>
- Implementation of creative ideas in the research network as well
as interdisciplinary work<br>
<br>
You will perform these tasks independently in coordination with
Professor Dr.-Ing. Wolfram Schenck. In addition, you will work in an
interdisciplinary team consisting of the research associates of the
other universities and other professors.<br>
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Requirements: <br>
- Master of Science from a university or university of applied
sciences in one of the following fields: computer science, data
science, electrical engineering, (bio-)mechatronics or cognitive
sciences with specialisation in data-based modelling, statistics or
machine learning<br>
- In-depth expertise in data collection and analysis, machine
learning, statistics, data mining and optimisation<br>
- First practical experience with the methods and toolboxes of
machine learning<br>
- Very good programming skills (Python, R, MATLAB/Simulink, etc.)<br>
- Excellent conceptual and analytical thinking and action<br>
- Independent and autonomous way of working<br>
- Outstanding intellectual capacity<br>
- Experience in writing academic texts and presenting scientific
work results<br>
- Very good knowledge of written and oral English<br>
- Excellent team spirit and communication skills, confident
demeanour<br>
<br>
Candidates are further required to make sure that their fixed-term
employment does not exceed the limits prescribed by the
Wissenschaftszeitvertragsgesetz due to previous employments.<br>
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The ideal candidate should also bring:<br>
- Basic knowledge of German language<br>
- Experience in project coordination<br>
- Experience in research activities, in the preparation of
scientific reports and publications or activities as a student or
research assistant<br>
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Benefits: <br>
- Opportunities for participation in qualification programmes<br>
- Support offers for publications and patents<br>
- University daycare facility “EffHa” and holiday care for
schoolchildren on Bielefeld Campus<br>
- 6 faculties with diverse partnerships and research collaborations
in one of the most economically powerful regions in Germany<br>
- Good accessibility by public transport<br>
- Participation in the university sports programme from Bielefeld
University<br>
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Bielefeld University of Applied Sciences has received multiple
awards for its successes in promoting equal opportunities and has
been certified as a family-friendly university. Therefore, women are
particularly welcome to apply, especially in the field of research
and in technology, IT and crafts. Applications from women will be
given preference in case of equal suitability, skills and
professional performance, unless reasons concerning the person of
another applicant predominate.<br>
<br>
Persons with severe disabilities are encouraged to apply, too.
Subject to other applicable laws, severely disabled applicants with
equivalent qualifications will be given preferential consideration.<br>
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Please find more detailed information on the SAIL subprojects at:
<a class="moz-txt-link-freetext" href="https://jaii.eu/sail">https://jaii.eu/sail</a>. Multiple applications for other subprojects in
the network are expressly welcome. In this case, please include the
reference numbers of the respective subprojects in your application.<br>
<br>
If you have any questions relating to the content of the position we
offer, please contact Prof. Dr.-Ing. Wolfram Schenck via e-mail at
wolfram.schenck[AT]fh-bielefeld.de.<br>
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** Are you interested? Please apply online only by 23 February 2023,
stating the reference number 03302. **<br>
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Application link:
<a class="moz-txt-link-freetext" href="https://app.fh-bielefeld.de/qisserver/rds?state=change&type=3&nextdir=sva/bwmsas&subdir=sva/bwm&moduleParameter=bwmSearchResult&next=TableSelect.vm&P_start=0&P_anzahl=100&navigationPosition=qissvaCareer%2Csvabwmstellenuebersicht&breadcrumb=sva_bwm_stellenuebersicht&topitem=qissvaCareer&subitem=svabwmstellenuebersicht">https://app.fh-bielefeld.de/qisserver/rds?state=change&type=3&nextdir=sva/bwmsas&subdir=sva/bwm&moduleParameter=bwmSearchResult&next=TableSelect.vm&P_start=0&P_anzahl=100&navigationPosition=qissvaCareer%2Csvabwmstellenuebersicht&breadcrumb=sva_bwm_stellenuebersicht&topitem=qissvaCareer&subitem=svabwmstellenuebersicht</a><br>
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