Translational Neuroimaging Postdoctoral Fellowship at Penn
We are recruiting a post-doc for a cross-disciplinary (neuroscience, radiology, psychiatry) research program in translational neuroscience that combines fMRI, TMS, pupillography, and behavior recordings in humans. Seek to better understand how non-invasive neuromodulation affects the brain and behavior in circuits relevant to neuropsychiatric illness. We are recruiting an individual with expertise in functional and structural MRI data analysis, including brain network analysis using graph theory. The effort is headed by Drs. Yvette Sheline and Desmond Oathes, and will involve collaborative work with other scientists at UPenn, neuroimaging data analysis using machine learning techniques and neuroimaging statistics.
To apply, please send a curriculum vitae, a statement describing research interests and relevant background and three letters of recommendations, as well as relevant reprints/preprints of research articles to: Dr. Yvette Sheline, firstname.lastname@example.org.
Dr. Sheline will be available to meet with applicants during the SfN annual conference in October
Penn adheres to a policy that prohibits discrimination on the basis of race, color, sex, sexual orientation, gender identity, religion, creed, national or ethnic origin, citizenship status, age, disability, veteran status, or any other legally protected class.
Strong applicants will have:
- High motivation and enthusiasm for scientific research.
- Ph.D. and relevant research experience in computational neuroscience, computational psychiatry, or related fields (e.g., computer science, engineering and physics).
- Excellent written skills, including evidence of successful manuscript writing (first-author publications) and publication productivity.
- Excellent organizational, interpersonal, and oral communication skills.
- Expertise in neuroimaging software (e.g., FSL, AFNI, FreeSurfer) for structural and functional MRI preprocessing.
- Strong mathematical and programming skills using Linux, Matlab, R, Python, etc. and relevant imaging statistics. Additional background in signal processing for psychophysiological data or electrophysiological recordings is a plus.
- Willing to learn TMS methods and to collaborate across labs.