A postdoc position devoted to the modeling of learning in deep cortical networks is available in our Computational Neuroscience labs at the University of Bern, Switzerland. Our research is focused on biologically realistic models of spatio-temporal processing in recurrent cortical networks and their relation to reinforcement learning, Bayesian computing, learning to learn, and neuromorphic implementations.
The position is available from January 1st, 2021, for 2 years (extendable through new funding). We offer a stimulating environment with three research groups in theoretical and computational neuroscience, along with experimental neuroscience at the same Department of Physiology (physio.unibe.ch/gruppen.aspx), as well as close collaboration with other labs in neuroscience, artificial intelligence and neuromorphic engineering.
Ideal candidates should have a strong background in computational neuroscience, machine learning, applied mathematics and/or physics. Please send your CV, publication list, letter of motivation and contact information for at least two references to Mihai Petrovici (mihai.petrovici@pyl.unibe.ch) and Walter Senn (walter.senn@pyl.unibe.ch). The position will remain open until filled.
