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Postdoctoral Associate – Yale Imaging and Psychopharmacology Lab Description: There is an opening for a Postdoctoral Associate interested in machine learning and neuroimaging of addictions within the Yale Imaging and Psychopharmacology Lab at Yale School of Medicine. The postdoctoral associate will join a diverse, interdisciplinary team committed to understanding the biological mechanisms of addictions and their treatments. The successful candidate will have an opportunity to work with large, longitudinal, multi-modal (clinical, behavioral, and imaging) datasets as well as to develop their own research questions within this conceptual and experimental framework. In addition to developing his or her own research program, the successful candidate will contribute to an NIH funded R01 combining machine learning and longitudinal modeling approaches to 1) identify neural networks predictive of early alcohol initiation and misuse and 2) chart the developmental trajectories of these networks over time in a large sample of youth (N>3,000) using data from three unique, proprietary and completed datasets. Other federally funded projects within the lab include acquisition of neuroimaging data from individuals with opioid-use disorder and pharmacological challenge studies. Thus, there are multiple opportunities for translational research. Qualifications: PhD, MD or MD/PhD in neuroscience, statistics, psychology, engineering or a related field is required. Previous experience working with neuroimaging and/or computational modeling is desired but not required. Candidates with strong statistical background but without neuroimaging experience are also strongly encouraged to apply. To apply: Please e-mail a brief letter of interest describing your current experience, skills, and how your future goals align with this position, along with an up-to-date CV and contact information for three references directly to [log in to unmask] Please also feel free to direct informal inquiries about this position to [log in to unmask] Recent lab publications: https://www.ncbi.nlm.nih.gov/pubmed/31719641 https://www.ncbi.nlm.nih.gov/pubmed/30283002 https://www.ncbi.nlm.nih.gov/pubmed/30606049 https://www.biologicalpsychiatrycnni.org/article/S2451-9022(19)30297-6/fulltext ######################################################################## To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1