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USDA-ARS Postdoctoral Research Opportunity: Development of Novel Vaccines for Poultry Viral Diseases
of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: You will be part of the research team learning about developing recombinant Marek's
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Center. The unit focuses on vaccinology, pathobiology, and diagnostics for emerging or re-emerging poultry viruses. Research Project: You will join a team developing vaccines against avian metapneumovirus
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on barley bacterial leaf streak, Fusarium head blight (FHB) and/or oat stem and crown rust disease research. Research activities may include conducting gene mapping and molecular marker development
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the unit. You will be part of the team which is evaluating and developing vaccines against HPAI. Currently, the US is experiencing one of the largest HPAI outbreaks and there has been serious consideration
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to develop genetic, genomic and molecular resources for for supporting the barley and oat research. Research Project: You will be involved with one of the two research projects: I. Barley genetics and
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and analyze trait measurements related to plant development, plant physiology, and seed yield under different irrigation regimes in two locations with different weather patterns. You will also aid in
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genomics, and pathogen discovery. The fellowship will focus on the development, evaluation, and application of advanced laboratory and sequencing approaches for the detection and characterization of known
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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