We seek a postdoctoral researcher with deep interest in human reinforcement learning and decision-making to work on the newly funded project:

Learning and Exploration under Perceptual and Value Uncertainty

Organisms often face the challenge of navigating a world riddled with many sources of uncertainty, be it ambiguous sensory inputs or unreliable behavioral outcomes. Most existing research only considered either of these two sources of uncertainty in the contexts of perceptual decision making for the former, and reinforcement learning and value-based decision making for the latter. The goal of the project is to develop a unifying experimental and theoretical account of human adaptive behavior subject to both perceptual and value uncertainty.

The post of 1-year is at the Institute of Neuroinformatics (ini.uzh.ch) of the University of Zurich and ETH Zurich, in close collaboration with Rafael Polania’s Decision Neuroscience Lab (decision.ethz.ch).

Preferable starting date: February 1st, 2020.

The post involves psychophysics and data-driven computational modelling. Candidates should have a PhD in cognitive science, psychology, neuroscience, computational science, or a related field. Preference will be given to applicants with prior experience in designing and conducting psychophysics experiments, in addition to having strong programming (MATLAB or python), computational and statistical skills.

How to apply:

Please write to Hazem Toutounji (hazem@ini.ethz.ch), using the email as a cover letter, preferably before December 9th, 2019. Later applications will be considered until the post is filled. The application should include CV, list of publications and preprints, and contact information of 1-3 potential referees, in addition to a short summary (max. 300 words) of most relevant paper, describing your contribution.