Postdoctorial Fellow in Computational Neuroscience

Several Postdoctoral Fellow positions in discovering MRI based phenotypes for improving personalized medicine and prevention of neuropsychiatric disorders are available immediately at the Computational Neuroscience Lab (http://cnslab.stanford.edu; PI: Kilian Pohl). The successful candidate will contribute to research and development in the rigorous multi-modal analysis of longitudinal, multi-center brain MR studies. The research projects are partially funded by the to the AI for Mental Health Initiative (https://ai4mh.stanford.edu), NIH, and other collaboration resources. The researcher will work in a multidisciplinary research environment closely collaborating and publishing with imaging, computer, and neuroscientists at Stanford University.

We are seeking highly motivated individuals who have demonstrated academic excellence, including publications in first-class journals and conferences. Successful candidates should have a PhD (or equivalent) in Computer Science, Neuroscience, or related fields. The applicant should be an expert in neuroscience (computational, behavioral, cognitive, or system). A strong background in machine learning, deep learning, and statistical methods for medical image analysis is seen as plus.

The Computational Neuroimage and Neuroscience Lab (http://cnslab.stanford.edu; PI: Kilian Pohl) is part of the Stanford initiative AI for Mental Health (https://ai4mh.stanford.edu), which aims to transform Psychiatry by replacing subject observations with object assessment resulting in more effective and accessible research and care. The CNS Lab performs multidisciplinary research focusing on developing deep learning technology to identify biomedical phenotypes specific to substance abuse, depression, sleep, HIV, and adolescent brain.