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seeds. This research will help to unravel key indicators of biological relevance during seed quality testing procedures and contribute to a healthy national and international seed trade economy. Learning
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Description *Applications are reviewed on a rolling-basis. ARS Office/Lab and Location: A postdoctoral research opportunity is currently available with the U.S. Department of Agriculture (USDA), Agricultural
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, the participant will learn HPC computing technologies and techniques in genomic epidemiology and machine learning to quantify drivers of IAV evolution in swine using data generated from IAV surveillance in human
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. market access. The approach will include metagenomics and bioinformatics to understand genetic diversity of the pathogen. Learning Objectives: During this project, the participant will be involved in
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information needed to inform management of the disease. Specific areas of investigation will be based upon the participant’s expertise and interest. Learning Objectives: Under the guidance of a mentor, the
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traits in oats. Participate in data collection and genetic analysis of FHB resistance. Write manuscripts and present research at scientific conferences. Learning Objectives: The participant will receive
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of incorporating sensors, spectroscopy, imaging, and machine learning techniques into the postharvest processing workflows and/or pre-harvest evaluation of food quality and safety. The participant will have the
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. Learning Objectives: The selected fellow in this project will have the opportunity to contribute and advance their knowledge and skills in wood products carbon related research that will involve maintaining