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position is a 12-month appointment with the possibility of renewal contingent upon satisfactory performance and the availability of funding. Minimum Qualifications: Education: PhD in the Biosciences or an MD
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Position Description: Every great life-changing discovery begins the same way—with new knowledge. It can change everything, from a single life to the future of entire communities. That’s why
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Experience with imaging data processing, anatomical or functional registration, and 3D planning/reconstruction for recording trajectories Required Application Materials: CV One-page statement of interest
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Position Overview School / Campus / College: College of Arts and Sciences Organization: Biology Title: Postdoctoral Position in Quantitative Cell Biology in the MATSU lab Position Details Position
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protected and open field cultivation systems Use lab and field equipment (ICP, HPLC, gas exchange analyzer, soil/root/plant sensors, chlorophyll fluorescence, etc.), data loggers and image processing tools
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record (EHR) as well as MyChart data, with the opportunity to work on applications of machine learning/deep learning/ Natural Language Processing in novel areas of healthcare. The position is open for a
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. Additionally, the position offers opportunities to work on brain imaging studies aimed at understanding the neural basis of cannabis and cannabinoids dependency. YC-SCAN² is currently conducting several NIH
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Title of the Position: Postdoctoral Associate – Cancer biology and genomics (Aitken Lab) Department and School: The Center of Molecular and Cellular Oncology (CMCO) and Department of Pathology, Yale
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investigators. Position Requirements Ph. D. in theoretical or physical chemistry, or a related field Extensive experience in one or more of the following areas: Computational modeling of homogeneous
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 13 days ago
Experience Requirements Applicants should have (or expect to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in machine learning, artificial intelligence, natural