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genomics techniques with computational analyses to understand gene regulation in health and disease. Such models are based on multi-omics high-throughput assays, either performed by the Postdoctoral
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research program addressing important and fundamental questions. To support this effort, interdisciplinary and translational approaches are encouraged. Qualified candidates must be a recent recipient of a
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are required. The ability to work both independently and collaboratively is also essential. Must be computer literate with proficiency and working knowledge of database and reporting tools such as Microsoft Word
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neuroscience research with clinical applications to addiction and other mental health concerns. Our work draws on methods from psychology, experimental economics, human neuroscience, and computational psychiatry
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documentation indication Ph.D program is completed. Proof to work in the US must be provided. Candidates should upload cover letter, detailed curriculum vitae including publication list, and contact information
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productivity, performance, and overall fit. The postdoctoral program enables associates to build a high caliber scholarly portfolio in social-structural determinants of health, intersectionality, and community
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experiences and individual differences, as well as cognitive modeling of decision-making in both lab and realworld settings. Successful candidates will be supported in building a research program at the
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crystallography and cryo-electron microscopy (cryo-EM) is desirable, however not required. The selected candidate will obtain appropriate training in crystallization and crystallographic computing, microscope
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-doctoral associate for an NSF-funded project on the social, environmental and linguistic factors that affect human wayfinding. Working with the PI and co-PIs in computer science, psychology, applied math and
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, excellent communication skills, excellent computer literacy. Certifications/Licenses Required Knowledge, Skills, and Abilities PhD in life sciences. Experience with proteomics, bioinformatics, mass