22 phd-position-in-database-modeling Postdoctoral research jobs at University of Virginia
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. This position offers a unique opportunity to contribute to high-impact, interdisciplinary research in generative AI systems. The successful candidate will work closely with Dr. Peter Beling and Dr. Tyler Cody and
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A Postdoctoral Research Associate position in advanced MRI acquisition, analysis, and modeling is available in the Department of Radiology at the University of Virginia School of Medicine, under
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and membrane protein complexes • Familiarity with Linux, MATLAB, Python, or other computational tools is a plus This position provides an excellent opportunity to work on high-resolution structural
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molecular, biochemical, and behavioral manifestations. We have collaborations with other labs that enrich the overall research experience. QUALIFICATIONS Applicants must have PhD and/or MD (or equivalent
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learning, small data learning · Active learning, Bayesian deep learning, uncertainty quantification · Graph neural networks This position involves active participation in a well-funded
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Research Associate position, with the possibility of extension based on an annual basis dependent upon satisfactory performance and the availability of funding. This position is part of the Preventive
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science of science, network science, and natural language processing. As part of a small research team, the postdoc will help lead efforts to provide a quantitative model of global competitiveness
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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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The Department of Genome Sciences at the University of Virginia is seeking a highly motivated candidate for a Postdoctoral Research Associate position in the Miller Lab . The successful candidate
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Research Associate. This position offers an excellent opportunity to work alongside Dr. Hong Zhu and a multidisciplinary research team, contributing to innovative methods in comparative effectiveness