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application of foundation models for fungal DNA and protein sequences. With ARS and external AI knowledge-holders, you will adapt long-context DNA language models to fungal genomes. These DNA-language models
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of unknown PFAS, supporting agricultural research and advancing the ARS mission. The project will involve compiling high-resolution mass spectrometry (HRMS) databases for PFAS, creating machine learning models
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invited to set up experiments to explore potential environmental conditions, test water mixing models, and constrain the influence of biology on mineral alteration. Studies focusing on clay minerals
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, presentations, and stakeholder-focused decision-support tools. Learn how modeling and data-driven research can support regenerative agricultural practices, soil health, and natural resource conservation. Mentor(s
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to artificial-intelligence-driven monitoring systems to forecast and manage stored product insect populations and insecticide resistance. Home to Kansas State University and The Flint Hills, Manhattan, KS
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: The U.S. Geological Survey (USGS) increasingly relies on efficient, scalable administrative processes to support its broad scientific mission across field, laboratory, and data-driven research environments