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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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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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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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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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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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Systems Safety Center of Excellence • Intelligent Transportation Systems Joint Program Office • Positioning, Navigation and Timing (PNT) & Spectrum Management • Office of Research, Development & Technology
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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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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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approaches used to support reliable pathogen detection. This project aligns with IDPB’s public health mission to develop, improve, evaluate, and apply laboratory technology to detect microbial agents