Job
Postdoctoral fellow
Organization
National Institute of Mental Health, Bethesda, MD and surrounding area
Scientific focus area
Neuroscience, Computational Biology
The Unit on the Neural Computations in Learning at the National Institute of Mental Health/NIH is looking for a creative and enthusiastic postdoctoral fellow to join the lab. Our research is focused on the computational neuroscience of reward prediction and learning. We study how timing, inference processes and goal selection impact learning in the brain during reward-guided tasks in animals and humans and how these processes change in compulsive behaviors and in addiction.
About the position
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.
Apply for this vacancy
What you'll need to apply
Applicants should send a brief research statement, CV, and the names of two academic references to Dr Angela Langdon.
Contact name
Angela Langdon
Contact email
Qualifications
Interested candidates should have a PhD in neuroscience, psychology or cognitive science, strong quantitative and programming skills and a record of scientific contributions in an area relevant to research in the lab.
Disclaimer/Fine Print
Selection for this position will be based solely on merit, with no discrimination for non-merit reasons such as race, color, religion, gender, sexual orientation, national origin, political affiliation, marital status, disability, age, or membership or non-membership in an employee organization. The NIH is dedicated to building a diverse community in its training and employment programs and encourages the application and nomination of qualified women, minorities, and individuals with disabilities.
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