Postdoctoral Associate Position in Human Neuroimaging

The Gabbay Laboratory within the Department of Psychiatry at the University of Miami Miller School of Medicine is seeking highly motivated postdoctoral scholars in the field of human neuroimaging. Available positions will focus on analyzing fMRI and proton MR spectroscopy data as well as acquiring or processing related MRI and biological measures. Candidates should either have completed or be near completing a PhD in neuroscience, psychology, cognitive neuroscience, radiology, engineering, biostatistics, or a related field, and should have a strong background in quantitative analysis. Proficiencies with at least one major neuroimaging software suite (e.g. FSL, AFNI, SPM, Freesurfer, Caret, Connectome Workbench, etc.) and Unix/Linux environment are expected. Familiarity with Matlab, Python, and/or R programming languages is a plus. The primary responsibilities for this postdoctoral fellow will be to run scans, analyze neuroimaging data from multiple ongoing and recently concluded research projects, and write manuscripts. Under the mentorship of Vilma Gabbay, MD and Benjamin Ely, PhD, postdoctoral scholars will be expected to advance clinical and methodological knowledge through their postdoctoral training. Our lab is dedicated to the study and treatment of mood, anxiety, and substance use disorders in adolescent and high-risk adult (e.g. HIV+) populations using innovative neuroimaging and immunological methodologies. The neuroimaging program features high-resolution data acquisition and analysis techniques modeled on the Human Connectome Project (HCP) and is committed to the highest standards for magnetic resonance imaging and spectroscopy. The lab is funded by four ongoing NIH R01 neuroimaging studies (R01MH120601, R01DA054885, R01MH128878, and

R01MH131207

) and several smaller grants, providing unparalleled funding for active and exploratory studies. Major research topics include longitudinal studies of adolescent mood and anxiety disorders; comorbidity of depression, cannabis use, and HIV infection; and an intervention study aimed at improving well-being among healthcare workers with parental responsibilities during the

COVID-19

pandemic. Project abstracts with further details can be found on NIH RePORTER. Resources available on-campus and through long-standing collaborations include multiple research-dedicated 3T MRI scanners (Siemens Skyra/Vida/Prisma) with cutting-edge accelerated and multi-echo fMRI sequences, high-performance scientific computing clusters, and an extensive library of analytic and statistical software. The PIs are fully committed to fostering the trainee's research independence through publication of first-authored manuscripts in top journals and mentorship in grant applications. In addition to assisting with the PI's proposals, the successful applicant will be highly encouraged to develop and pursue funding for their own research project through federal (e.g. NIH F32) or foundation grant programs by the end of their first year. Proficiencies with at least one major neuroimaging software suite (e.g. FSL, AFNI, SPM, Freesurfer, Caret, Connectome Workbench, etc.) and Unix/Linux environment are expected. Familiarity with Matlab, Python, and/or R programming languages is a plus.