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Regular Job Code 9546 Employee Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job 70% Data analysis: develop software tools for analysis of multivariate neural data. Apply tools
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and production of software tools for in silico screening of chemical libraries and rational drug design of molecules for therapeutic purposes. - Contribute to the development of a high-throughput
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 hours ago
and leadership team in strategic planning to enhance ITR’s scientific productivity, analytic capacity, and research infrastructure Minimum Education and Experience Requirements Doctoral degree (PhD
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Posting Details Position Information Position Title Associate Dean for Academic Affairs, School of Nursing Department School of Nursing Posting Number F260026 Posting Link https
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advanced quantitative analyses, lead scientific reporting, and participate in the ethical and governance process of collaborative epidemiological research. Working within an active multidisciplinary team
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to collaborate effectively with colleagues and project partners. Specifically, you have: Education: A PhD in a relevant field, with knowledge of structural mechanics, masonry mechanics, nonlinear finite element
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about the ILR School can be obtained at our web site, http://www.ilr.cornell.edu and CAROW at https://www.ilr.cornell.edu/carow . Requirements: Applicant must have a PhD in labor relations, sociology
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look forward to receiving your application! We are looking for a PhD student for sustainable and resource-efficient machine learning. Your work assignments Machine learning has recently advanced through
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the Separations Science group. Our group is conducting research to enable cost-effective processes for biorefineries. The initial appointment is for one year, with possible renewal for up to three years
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision