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emphases in the areas of traffic safety, operations, highway design, and the application of statistical and econometric methods to transportation data. The successful applicants will serve in a
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successful candidate will join the Bridge Lab to conduct data-intensive and collaborative lake and stream ecology research and translate results into action in partnership with communities. The postdoc
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in irrigated agricultural systems. The successful candidate will integrate field-based geophysical measurements with hydrologic data and modeling approaches to improve understanding of water quantity
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Position Summary The Data-Driven Research & Innovation in Veterinary Epidemiology Lab (DRIVE lab) at the at the College of Veterinary Medicine at Michigan State University is seeking applicants for a
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> on research projects related to kinetic equation and its related multiscale model reduction, numerical method, and data-driven/machine-learning approaches, including: • Numerical simulation of kinetic
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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, develop and optimize advanced MS methods in metabolomics (including EAD workflows), data analysis and support collaborative studies with Henry Ford Health. Detailed description of work/duties: Research
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agricultural drainage. The selected candidate will install, calibrate, maintain, and troubleshoot sensors and monitoring equipment; configure data loggers and telemetry systems; download and organize
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amounts of geospatial training data to effectively classify grazing, haying, and other grassland management regimes on U.S. agricultural lands. The researcher will also work closely with colleagues at
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aspects of socio-technical systems. Data science skills and an interest in spatial modeling are highly desirable. Experience with multi-disciplinary teams deploying mixed methods in complementary ways