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Field
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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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objective of ATMRI is to support research and innovation in air traffic management. ATMRI focuses on developing practical and data-driven solutions for complex aviation systems, in close collaboration
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objective of ATMRI is to support research and innovation in air traffic management. ATMRI focuses on developing practical and data-driven solutions for complex aviation systems, in close collaboration
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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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and industry collaborators. These deployments generate live data streams and provide a unique foundation for infrastructure-backed digital twins. This position emphasizes real-time rendering, engine
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infrastructure across gynecologic cancer research initiatives. The fellow will lead the development of multi-omics data integration, interactive visualization tools, and AI-assisted clinical decision
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industry collaborators. These deployments provide a rare opportunity to construct digital twins grounded in operational infrastructure, live data, and scalable computation. This position is not focused
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, analyze agronomic datasets, and develop interactive web-based decision-support tools using R and Shiny applications. Unit URL https://www.uidaho.edu/agricultural-life-sciences/academics/plant-sciences
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other regionalized GCAM variants, as well as other integrated assessment or earth system models, is highly desirable. Advanced programming skills in R and Python for data processing and visualization