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affect oyster phenotypes targeted for improvement. The fellow will also gain experience using advanced computational methods to develop tools that can accurately predict desirable phenotypes. With
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to, big data mining, protein structure and function prediction, protein-ligand interaction, molecular modeling, molecular toxicology, workflow development, gene knockout design and optimization, and genetic
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this information can improve our ability to predict the spread and intensity of wildfires and prescribed fires. Learning Objectives: The program participant will learn a variety of new skills to measure
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abiotic factors affect the survival of beneficial/pest insects under, and in response to, varying abiotic conditions to better predict changes in their spatial distribution across agricultural and
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survival data to predict the likelihood and extent of bacterial contaminant introduction, persistence, and transfer in the dairy system. Intervention Strategy Development and Optimization: Utilize advanced
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given to candidates located in, or willing to relocate to Fort Collins, Colorado. The USGS mission is to monitor, analyze, and predict current and evolving dynamics of complex human and natural Earth