Scientific ; m​/f​/d - Theoretical Neuroscience

The Dept. of Theoretical Neuroscience, in particular, develops novel AI and machine learning methodologies for neuroscience and psychiatry, as well as for dynamical systems modeling and time series analysis more generally.

We have openings for several fully-funded positions (PhD & Post Doc) at the intersection of AI/ML, dynamical systems, and neuroscience within a BMFTR-funded Neuro-AI consortium, situated at Heidelberg University & Central Institute of Mental Health Mannheim (Germany).

The idea is to develop and train AI foundation models for reconstructing from massive multiple single-unit, Ca2+ imaging, and behavioral data the computational systems and plasticity dynamics underlying flexible rule, in-context, and continual learning in animals. In a second step the results are to be used to improve AI models for learning and out-of-domain generalization in continuously changing environments, and to be applied in mental health.

Please find links to some relevant publications below.

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