Connectionists: [jobs] Doctoral Researcher - Transparent Interpretable Neural Robots

[Stefan Wermter]

At the University of Hamburg, Dept of Informatics, Knowledge Technology, 
we are looking for 1 additional Doctoral Candidate Researcher (PhD 
students)  in neural network technology, intelligent robotics and 
transparency/explainability in artificial intelligence.

Project: TRAIL: TRAnsparent InterpretabLe robots (Doctoral Network, EU 
MSCA Project)
Start date: 1.10. 2023 or as soon as possible, for 3 years
Salary level: salary in accordance with the attractive EU MSCA Doctoral 
Network regulations for doctoral candidates
Application deadline: 26 July 2023

The Doctoral Network TRAIL consists of 15 institutions including 
universities, research institutions and industry partners. The research 
area of TRAIL is neural network technology, intelligent robotics and 
transparency in artificial intelligence and is coordinated by 
Universität Hamburg. The focus of the research at Universität Hamburg is 
on neural networks and explainability for interactive social robotics. 
The position will be filled in the context of transparency and 
interpretation of neural networks for interactive cognitive robots.  The 
researcher will focus on the following indicative topics: Interpretable 
representations in deep learning architectures or automated 
interpretation of neural mappings for cognitive robotics.

The successful candidate will receive an attractive salary in accordance 
with the MSCA regulations for Early-Stage Researchers. The exact (net) 
salary will be confirmed upon appointment and is dependent on local tax 
regulations and on the country correction factor (to allow for the 
difference in cost of living in different EU Member States). The salary 
includes a living allowance, a mobility allowance and a family allowance 
(if applicable). Furthermore, TRAIL will offer to take advantage of 
joint scientific research trainings, transferable skills workshops, and 
international conferences. For more information about the project and 
consortium see 
https://www.inf.uni-hamburg.de/en/inst/ab/wtm/research/trail.html

Requirements:
MSc or demonstrated equivalent in Artificial Intelligence, Computer 
Science or Engineering with a focus on Intelligent Systems, Intelligent 
Robotics or Neural Networks is required. Excellent programming skills 
(Python, C++, PyTorch, Machine Learning Frameworks, ROS etc.) are needed 
and expertise in at least one of neural networks or intelligent robotics 
is needed. Publications are a desired advantage. The posts involve 
substantial traveling within Europe. Each PhD student will be expected 
to spend secondments at other partner sites and travel to international 
conferences. According to EU mobility rules, the doctoral researcher 
must not have resided or carried out their main activity (work, studies, 
etc.) in Germany for longer than 12 months in the 3 years immediately 
prior to their recruitment. Applicants who already have a doctoral 
degree are NOT eligible and should NOT apply. Excellent English 
communication skills are an important requirement.

Application:
Upload your complete application documents (cover letter, curriculum 
vitae with details about where you resided or carried out your main 
activity [work, studies, etc.] in the three years immediately prior to 
the application deadline, copies of degree certificate[s], names and 
email contacts for two referees who would be willing to write a letter 
of support for your application, any English language certificates) via 
the online application form only.

For more details on how to apply please go to:

https://www.uni-hamburg.de/stellenangebote/ausschreibung.html?jobID=e66be09393962951c113a5d0ef89eba57fb6c6cd


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Professor Dr. Stefan Wermter
Director of Knowledge Technology
Department of Informatics
University of Hamburg
Vogt-Koelln-Str. 30
22527 Hamburg, Germany

Email: stefan dot wermter AT uni-hamburg.de
https://www.informatik.uni-hamburg.de/WTM/
https://www.informatik.uni-hamburg.de/~wermter/

***********************************************








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