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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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, data analysis, and visualization environments/IDEs (e.g., R/R Studio, Python/Spyder/VSCode) Familiarity with GIS methods and cloud-based computing resources (e.g., Google Earth Engine) for large-scale
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visualization, data organization and facilitating communication of results between research teams Active collaboration with experimental research groups working in drug discovery Communication of results in
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environmental data visualization Familiarity with soil and water sampling, laboratory analytical methods, chain-of-custody procedures, and field or laboratory quality assurance and quality control
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Python and R programming for statistical modeling, data visualization, and integration of large-scale genomics datasets Participate in the design of strategic data acquisition plans to support ongoing