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of compressible flow regimes, including supersonic and hypersonic flows, as demonstrated by application materials. Familiarity with machine learning or data-driven modeling approaches in fluid dynamics, as
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machine learning methods. Provide theoretical predictions to guide experiments, and atomic-scale physical understanding to experimental observations. Publishing findings in peer-reviewed journals
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detector operations, data analysis, event simulation, and publication of research results. Job Description Conduct research in experimental nuclear physics with members of the University of Kansas CMS
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participation in relevant facets of the group's research endeavors ranging from data analysis, software development, publication preparation, grant proposal preparation, editorial work, presentation of results
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of occurrence rate measurements. This also entails participation in relevant facets of the group’s research endeavors ranging from data analysis, software development, publication preparation, grant proposal
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validate polarizable force field models. Responsibilities will include both macroscopic property analysis (e.g., density, diffusion coefficients, ion conductivity, interfacial tension) and atomistic-level
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Description 30%: Develop public health analysis tools to assess impacts of drinking water sources and groundwater quality on public health outcomes. 35%: Use modeling tools and data analysis to conduct research
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appropriate data collection and analysis documentation, providing written reports on research progress, and participating in research group meetings when asked. 25% - Disseminate research findings by 1
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% - Carry out primary, NIGMS-relevant research in a supportive, mentored environment. Projects will vary depending on the research group the successful candidate joins. Candidates will learn both domain