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are not limited to, Developing new computational methods and analytical tools, with particular emphasis on machine learning and artificial intelligence approaches. Identifying signatures of viral adaptation
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Organization U.S. Department of Agriculture (USDA) Reference Code USDA-ARS-SEA-2025-0213 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete application consists of: An application Transcript(s) – For this opportunity, an unofficial...
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Organization U.S. Department of Agriculture (USDA) Reference Code USDA-ARS-SEA-2025-0158 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete application consists of: An application Transcript(s) – For this opportunity, an unofficial...
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Raman imaging technologies for safety and quality evaluation of agricultural products. Learn artificial intelligence/machine learning methods to evaluate hyperspectral image data to assess safety and
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of the relevant fields (Biology, Biochemistry, Cellular and Molecular Biology, Neuroscience, Veterinary Science, Veterinary Microbiology, Artificial Intelligence, or related field). Degree must have been received
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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 artificial intelligence (AI) and machine learning, to help
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mentor, the postdoc research fellow will participate in collaborative research to develop knowledge bases of the behavior, ecology, physiology, and genetics of invasive insect pests and their natural
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-system interactions and to deliver actionable intelligence at scales and timeframes relevant to decision makers. As the Nation's largest water, earth, and biological science and civilian mapping agency
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human and natural Earth-system interactions and to deliver actionable intelligence at scales and timeframes relevant to decision makers. As the Nation's largest water, earth, and biological science and