3 PhD positions in computational neuroscience

Applications are invited for three PhD student positions . The positions are funded by a grant from the Swiss National Science Foundation which is entitled "Why Spikes?".

This project aims at answering an almost 100 year old question in Neuroscience: "What are spikes good for?". Indeed, since the discovery of action potentials by Lord Adrian in 1926, it has remained largely unknown what the benefits of spiking neurons are, when compared to analog neurons. Traditionally, it has been argued that spikes are good for long-distance communication or for temporally precise computation. However, there is no systematic study that quantitatively compares the communication as well as the computational benefits of spiking neuron w.r.t analog neurons. The aim of the project is to systematically quantify the benefits of spiking at various levels.

The PhD students and post-doc will be supervised by Prof. Jean-Pascal Pfister (Theoretical Neuroscience Group, Department of Physiology, University of Bern).

The PhD candidates (resp. post-doc candidate) should hold a Master (resp. PhD) degree in Physics, Mathematics, Computer Science, Computational Neuroscience, Neuroscience or a related field. She/he should have keen interests in developing theories that can be tested experimentally. Preference will be given to candidates with strong mathematical and programming skills. Expertise in stochastic dynamical systems, point processes, control theory and nonlinear Bayesian filtering will be a plus.

The applicant should submit a CV (including contacts of two referees), a statement of research interests, marks obtained for the Master to Jean-Pascal Pfister (jeanpascal.pfister@unibe.ch ).

The position is offered for a period of three years and can be extended. Salary scale is provided by the Swiss National Science Foundation. Deadline for application is the 31st of January 2023 or until the position is filled.

Prof. Dr. Jean-Pascal Pfister
Theoretical Neuroscience Group
Bühlplatz 5
3012 Bern