The Hallquist lab is moving to the University of North Carolina in July 2020. We are seeking applications for a post-doctoral scholar to support two lines of funded research. The first examines learning processes that underlie interpersonal dysfunction and suicidal behavior in borderline personality, focusing on the interplay of Pavlovian and instrumental learning. The second examines dynamic variation in mood using a mathematical model of learning from rewards and punishments in daily life. Fellows will have ample opportunities to develop independent research projects and to publish empirical papers on suicide and borderline personality disorder using existing data. Ideally, applicants should have experience with both functional neuroimaging and the development of reinforcement learning or computational models of behavior. Postdocs will work on NIH-supported lines of research in close collaboration with Dr. Alex Dombrovski’s Decision Neuroscience and Psychopathology Lab at the University of Pittsburgh.
Funding is available now with a flexible start date. Applications will be reviewed on an ongoing basis. This is a one-year appointment with the possibility of extension. The ideal candidate will have strong quantitative skills, experience in cognitive, social, affective, or computational neuroscience, and an interest in decision-making in psychopathology. The position will include opportunities to develop and lead new research within the broader aims of the lab and guidance in obtaining independent funding. The lab environment is highly collaborative and postdocs have the opportunity to learn reinforcement learning modeling and functional imaging techniques.
Educational Requirements PhD in neuroscience, psychology, economics or a related field, or MD.
Qualifications and Experience Experience using advanced statistical and modeling approaches. Demonstrated ability to complete projects as evidenced by first-author publication(s). Programming skills are essential, particularly in functional programming languages including R, Python, or MATLAB. Preferred: Background in functional magnetic resonance imaging (including experience with AFNI, FSL, or SPM) or other human neurophysiology techniques.