Student Research Assistant (HiWi) (m/f/d)
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Stellenangebot vom 6. Mai 2026
The Department of Computational Neuroscience investigates how neural systems support learning and adaptive behavior, with a particular focus on navigation and goal directed decision making. This project examines how hippocampal place cells reorganize when goals or environmental contexts change—a phenomenon central to rapid navigation. Two leading hypotheses propose that this reorganization is driven either by spatial prediction errors or by reward prediction errors. The project combines reinforcement learning models with behavioral and hippocampal neural data to evaluate these competing mechanisms.
We invite applications for a
Student Research Assistant (HiWi) (m/f/d)
starting at your earliest convenience. The contract will run for a duration of at least 3 months (with the possibility of extension), and the weekly workload can be negotiated flexibly with the maximum of 20 hours.
Responsibilities:
1. Assist in developing reinforcement learning agents that optimize spatial or reward based learning signals.
2. Assist in analyzing behavioral and hippocampal datasets to assess which computational mechanism aligns with empirical evidence.
3. Assist in building additional simulation pipelines and exploratory data analysis.
Reference:
Kumar, M.G. et al. (2025). A Model of Place Field Reorganization During Reward Maximization. ICML. https://proceedings.mlr.press/v267/kumar25a.html.
Qualifications:
4. Matriculated at a German university.
5. Strong quantitative background at a BSc or MSc level in Neuroscience, Computer Science, Cognitive Science, Math, Physics, Engineering, or related computational fields.
6. Proficiency in Python and experience with PyTorch or JAX.
7. Prior exposure to reinforcement learning is advantageous.
What we offer:
The successful candidate will work in a cutting-edge international lab at the Max Planck Institute for Biological Cybernetics. The candidate will have the opportunity to develop their skills and advance their career through hands-on experience in theory-driven reinforcement learning models and analyzing experimental datasets while working closely with the research community in the Max Planck Institute and beyond. Remuneration will be based on qualifications and working hours.
How to apply:
If you are interested in the position, please send your CV (PDF, no photo of yourself), outlining your qualifications and experience, as well as names and contact information of at least two referees, to M Ganesh Kumar (ganesh.kumar@tuebingen.mpg.de) with the subject “HiWi-MPI-KYB”.
If you have additional questions, please e-mail Ganesh.
The Max Planck Society is committed to employing diverse individuals and strives for gender equity and diversity.
We welcome applications from all backgrounds and explicitly encourage members of underrepresented groups to apply.
The role will be filled on a rolling basis.