Joint Columbia/NIMH postdoctoral position
We are seeking a post-doctoral fellow (or equivalent) to be co-supervised by Elizabeth Hillman at Columbia University’s Zuckerman Institute and Peter Bandettini at the National Institute of Mental Health Intramural Research Program. This position requires expertise in dynamic data analysis and a strong interest in exploring the neural basis of functional magnetic resonance imaging. fMRI data acquired in humans will be compared to mouse wide-field optical imaging of neural activity and hemodynamics to test and inform improvements in fMRI data analysis, particularly in relation to resting state functional connectivity mapping methods. The individual may have a computational, neuroimaging or engineering background, with a preference for prior experience in fMRI analysis. This position could be a postdoctoral fellowship or for someone without a doctorate who has relevant skills and experience.
The position could be geographically located in either New York or the Washington DC area.
The Hillman lab (https://zuckermaninstitute.col... ) within Columbia’s new Zuckerman Mind Brain Behavior Institute is an energetic, diverse group with broad interests spanning imaging technology development and its application to answering novel questions relating to real-time brain activity and its relation to behavior across the scales and species. Our neurovascular coupling work seeks to better inform the interpretation of human fMRI data in health and disease through elucidation of the mechanistic underpinnings of the BOLD signal.
Dr. Bandettini’s Section on Functional Imaging Methods at the National Institutes of Health (https://fim.nimh.nih.gov/ ) is a team of physicists, psychologists, engineers, neuroscientists, and computer scientists committed to advancing the field of fMRI by developing of improved fMRI data acquisition and processing methodology, shedding light on the relationship between neuronal activity and hemodynamic changes, characterizing the sources of artifact and useful information in the signal, and bridging the gap between basic development and research and clinical applications.
Interested applicants should submit their Curriculum Vitae, cover letter and list of references to: Elizabeth.email@example.com, firstname.lastname@example.org, and Dan.Handwerker@nih.gov
Women and minorities are strongly encouraged to apply.
Machine Learning Group
Data Science and Data Sharing Group