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, game-theoretic analysis, network problems, decision analysis, or behavioral economics Proficiency in a scientific computing or statistical programming languages (e.g., Python, R, Julia, C++, or MATLAB
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genomics and II. Barley and oat molecular biology. For the first project, you will help conduct genetic analysis of resistance to stripe rust and hessian fly in barley and map the key genes or QTLs related
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, integration, and analysis of large, diverse datasets that benefit from high-performance computing (HPC). The objective of these fellowships is to facilitate cross-disciplinary, cross-location research through
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well as communicate with research networks within the scientific community. Learning Objectives: As part of this learning experience, you may: Learn how grapevine populations and germplasm are evaluated to identify
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on participation in animal study design, preparation, and execution. Post-collection processing and analysis of animal specimens may also be performed through laboratory assays (e.g. nucleic acid extractions, RT
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problems that also depend on collaboration across scientific disciplines and geographic locations. In addition, many of these technologies rely on the synthesis, integration, and analysis of large, diverse
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variety of meteorological and snowpack sensors. Learn to document avalanche activity and environmental conditions using standardized protocols. Data Analysis and Modeling Train to process and analyze