We have an opening for a postdoctoral fellow to join my lab at the National Institute of Mental Health at the NIH campus in Bethesda, MD. Research in the lab is focused on the computational neuroscience of reward prediction and learning. Broadly, we study how timing, inference processes and goal selection modulate learning in reward-guided tasks in animals and humans, and how these processes are instantiated in neural activity across the reward learning circuits of the brain. Our goal is to understand how reward learning is altered in compulsive behaviors, addiction, and motivational deficits in disorders of mental health. We are looking for a postdoc who is interested in developing approaches from reinforcement learning, dynamical systems theory, and Bayesian inference to understand the online regulation of reward prediction and learning in neural activity and behavior. We work with a broad network of collaborating labs that span rodent, NHP and human studies, and the ideal candidate will be comfortable working in a highly interdisciplinary environment to pursue novel and translational insights into the neural basis of reward learning. This opening is an excellent opportunity for a computational neuroscientist who wishes to apply theoretical ideas to understand empirical data, with the opportunity to collaborate on novel paradigms to test computational models of reward-guided behavior and reward learning in the brain.
