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, Python, GitHub, fieldwork, laboratory workflows, or grant/manuscript development. Experience with R, Git/GitHub, phylogenomic or population genomic workflows, GIS/spatial analysis, herbarium curation
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scenarios. The researcher will develop profit–risk–environment tradeoff products, build reusable R/Python workflows, and publish and present results in collaboration with USDA-ARS and university partners
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of hydrologic processes, transboundary/shared water resources management, and coupled human–natural systems. Proficiency in geospatial and scientific computing tools (e.g., Python, R, GIS, Google Earth Engine
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remote sensing and UAV flight operations. Proficiency with photogrammetry and GIS software (e.g., Pix4D, Agisoft Metashape, ArcGIS, QGIS). Strong data analysis skills using Python, R, or similar analytical