The research group of Prof. Dr Sen Cheng at the Institute for Neural Computation (INI), Ruhr University Bochum is looking for a highly motivated Student Assistant (6-8 h/week) with excellent programming skills to lend support to a project focused on modeling spatial navigation using techniques from deep reinforcement learning. The successful candidate will have the opportunity to acquire experience in the use of deep reinforcement learning models as well as techniques to analyze and interpret deep neural networks.
The Ruhr University Bochum is home to a vibrant research community in neuroscience and cognitive science. The Institute for Neural Computation combines different areas of expertise ranging from experimental and theoretical neuroscience to machine learning and robotics. For further information see: www.rub.de/cns
How to Apply
Please send your application, including CV, academic transcripts and letter of motivation, as a single PDF file to Vinita Samarasinghe (email@example.com).
Candidates must be enrolled at a German university to be eligible for this postion.
What we are looking for:
Good Python programming skills
Experience using Gitlab for version control
Good written and spoken English
Good communication skills and ability to work in a team
Further assets :
Basic knowledge of reinforcement learning and/or deep neural networks
Basic knowledge of computational neuroscience
The position is available immediately and is initially limited for 3 months with the possibility of extension.
Ruhr University Bochum is committed to equal opportunity in employment and gender equality in its working environment. To increase gender distribution in all job categories and at all levels, we strongly encourage applications from qualified women. Female applicants will be given preferential consideration when their level of qualification, competence and professional achievements equals that of male candidates, unless arguments based on the personal background of a male co-applicant prevail. Applications from appropriately qualified handicapped persons are also encouraged.