The Unit on the Neural Computations in Learning at the National Institute of Mental Health/NIH, led by Dr Angela Langdon, is looking for a creative and enthusiastic postdoctoral fellow to join the lab!

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. We have a particular interest in how reward learning is altered in compulsive behaviors and in addiction.

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 have 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 learning in the brain.

Interested candidates should have strong quantitative and programming skills, a background in neuroscience, psychology or cognitive science and a record of scientific contributions in an area relevant to research in the lab. Applicants should send a brief research statement, cv and the names of two academic references to Dr Angela Langdon (angela dot langdon at nih dot gov). Informal enquiries are welcome!