Dear all, I am looking for five people to join my group at the Campus Institute Data Science (CIDAS), University of Göttingen, Germany. We study how the brain builds and uses its internal model of the world, and how those principles can be reengineered in artificial neural networks. In parallel, we run a clinical line of work on epilepsy, applying machine learning tools to intracranial recordings from patients, together with the University Hospital Frankfurt. All positions are based in Göttingen and start as soon as possible. PH.D. STUDENT - HIPPOCAMPAL REPRESENTATIONS IN DYNAMIC ENVIRONMENTS TV-L E13 100%, 3 years Analyse an unpublished, large-scale in-vivo miniscope dataset: CA1 pyramidal cells tracked across 11 tasks and 34 days. Characterise how cognitive maps emerge, drift and are reused, from single cells to the geometry of the population manifold. In close collaboration with Tom McHugh (RIKEN CBS, Japan). PH.D. STUDENT - BRAIN-INSPIRED WORLD MODELS FOR DYNAMIC ENVIRONMENTS TV-L E13 100%, 3 years We distil inductive biases from normative hippocampus models and use these insights to build novel and powerful model-based deep RL agents. The goal: agents that plan over long horizons with interpretable internal representations. POSTDOCTORAL RESEARCHER - MACHINE LEARNING FOR EPILEPSY TV-L E13 100%, ~1 year with potential extension We try to predict epilepsy before it even starts. We use unique intracranial recordings from patients who suffered a bleed on the brain's surface, about one in three of whom go on to develop epilepsy. On these data we fine-tune EEG foundation models. We also build digital twin network models of individual patients, allowing us to simulate personalised prevention and treatment strategies. A collaboration with Michael Strüber and Felix Rosenow (University Hospital Frankfurt), and Richard Gao (Goethe University Frankfurt). RESEARCH ASSISTANTS (2 POSITIONS) Part-time, students welcome Support the projects above with calcium imaging data processing, behavioural tracking, software engineering and simulation experiments. A good entry point for a B.Sc. or M.Sc. thesis in the lab. PREREQUISITES Strong quantitative skills, fluency in Python, experience with machine learning, and genuine curiosity about both brains and machines. WHAT WE OFFER An interdisciplinary group at the interface of neuroscience and AI, a strong national and international network, and a generous ERC travel and publication budget for conferences such as NeurIPS, Cosyne and FENS. HOW TO APPLY Send your CV, a short motivation letter naming the position you are interested in, and contact details of two references to tristan.stoeber@posteo.net. Applications received by 24 September 2026 will receive full consideration; the positions remain open until filled. Internships and thesis projects outside these openings are always welcome. If you are unsure which position fits you best, or would like to hear more about a project before applying, write to me at the same address. I am happy to talk first. More about the lab at [1]. Best regards, Tristan [1] https://tristanstoeber.github.io -- Tristan Manfred Stöber, Ph.D. Computational Neuroscientist CIDAS Fellow, Campus Institute Data Science, University of Göttingen Research Fellow, Dept. of Neurology, University Hospital Frankfurt