Description: The Daw lab at the Princeton Neuroscience Institute is looking for a highly motivated postdoctoral research associate or more senior researcher to work on an NIH-funded multi-lab collaborative project studying the neurocomputational basis of reinforcement learning in rodents. The project, in collaboration with the Berke and Frank labs at UCSF, combines advanced system neuroscience and computational modeling techniques to study planning in rodents engaged in dynamic spatial foraging tasks. The successful candidate will develop computational models of reinforcement learning in the brain and leverage these models to assist the experimental groups with experimental design and multimodal data analysis of neurophysiological, causal, and behavioral data. Essential qualifications for this position include: a Ph.D. in Neuroscience, Psychology, Cognitive Science, Computer Science, Engineering, or other related field, and strong experience with computational models, programming, and quantitative methods. Preferred qualifications include experience in reinforcement learning, neural networks, and/or statistics. Questions can be addressed to Professor Nathaniel Daw, ndaw@princeton.edu. Review of applications will continue until the position is filled. The Term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory performance and continued funding; those hired at more senior ranks may have multi-year appointments. Interested applicants must apply online at https://puwebp.princeton.edu/AcadHire/position/37022 and include a cover letter stating background and research interests, a curriculum vitae including a full publication list, and contact information of at least two references. The work location for this position is in-person on campus at Princeton University. This position is subject to the University's background check policy.
