Connectionists: Postdoc position on Biological Deep Learning

[Walter Senn]

Dear all
One postdoc position devoted to learning in deep cortical networks is available in the Computational Neuroscience labs at the University of Bern, Switzerland. Our research is focussed on biologically realistic models of spatio-temporal processing in recurrent cortical networks and their relation to reinforcement learning, Bayesian computing, and neuromorphic implementations. The position is focussed on formalizing the dendritic processing of cortical pyramidal neurons, in particular on combining top-down and bottom-up information streams within pyramidal neurons, and in integrating these neurons in deep networks.    

The position is part of a collaboration with Profs Fritjof Helmchen and Giacomo Indiveri (UniZH / ETHZ) supported by the Swiss National Science Foundation and is available from January 1st, 2021, for 2 years (extendable). 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 <file:///Users/walter/Documents/Walter_Physio/admin/ownPositionAnnouncments/HBP_PosAnnouncments2020/physio.unibe.ch/gruppen.aspx>), as well as close collaborations 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 Walter Senn (walter.senn at unibe.ch <mailto:walter.senn at unibe.ch>) and Mihai Petrovici (mihai.petrovici at unibe.ch <mailto:mihai.petrovici at unibe.ch>), with cc to Virginie Sabado (virginie.sabado at unibe.ch <mailto:virginie.sabado at unibe.ch>). The first evaluation round will begin on November 8, 2020. The positions will remain open until filled.

With best regards,

Mihai Petrovici and Walter Senn

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