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, 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 (ML), to help solve complex agricultural
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primary learning experiences. You will examine the susceptibility of table grape breeding lines to gray mold caused by Botrytis cinerea, including developing and conducting scalable, high-throughput
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to evolutionary time scales. One of the goals of the SCINet Initiative is to develop and apply new technologies, including AI and machine learning (ML), to help solve complex agricultural problems that also depend
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. The Functional Foods Research (FFR) unit in Peoria, Illinois aims at developing bioactive food ingredients
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reporting, and develop practical tools and infrastructure for laboratory scientists. You will collaborate with bioinformaticians, laboratorians, epidemiologists, data scientists, and other public health
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participant to train on public health activities related to environmental health assessments, data analysis, community engagement, and scientific communication. The appointment will provide structured research
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will be a part of data collection, analysis, modeling and simulation for this project. Learning Objectives: Under the guidance of a mentor, you will have the opportunity to learn about drug development
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the development of new and enhanced technologies that support vegetable pickling, by fermentation or acidification, in the USA, under the USDA-ARS National Program 306, Quality and Utilization of Agricultural
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-making under uncertainty relevant to security and defense settings. Research activities will focus on methodological innovation, theoretical development, and applied mathematical/statistical modeling. Why
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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