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scales, from the genome to the continent, and sub-daily to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning
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problem-solving skills Experience developing, testing, and refining machine learning models Excellent written and oral communication skills Experience with publishing in peer-reviewed journals Stipend
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can be associated with biosignatures, thus, developing a more complete reference frame of alteration history and biological influence is critical for the search for potential biosignatures in
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scientists to enhance open-source watershed models widely used in agricultural research and management. The new data products, methods, and model improvements developed through this collaboration will be
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for Grain and Animal Health Research in Manhattan, KS. Our mission is to develop economical, effective, and ecologically sound methods for managing insect pests of grain and processed commodities, improve
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models and automation frameworks, assess workflow needs in collaboration with program staff, and develop functional prototypes that demonstrate measurable improvements in administrative efficiency