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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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post-harvest management practices, and develop methods to rapidly evaluate grain quality, using a combination of cutting edge tools, such as chemical ecology, molecular biology, and genomics
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virus genomics, bioinformatics, data science, and scientific computing. The fellowship will focus on using genomic and laboratory data to strengthen respiratory virus surveillance, improve analytical
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genetic, genomic, and phenotypic datasets, to support research and crop improvement. Basic and applied research is also conducted within this project. You will use methods in computational biology to
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collaborating with USDA-ARS scientists on research programs focusing on understanding the molecular, genetic, and genomic basis of traits of interest and applying the molecular genetics and genomics tools
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are to enhance barley and oat productivity, quality, and stress resilience by combing traditional, molecular, and genomics methods. You will collaborate with other scientists in the unit and other institutes
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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: Research will be focused on the development of bioinformatic and genomics tools
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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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conducting a Genome Wide Association Study to identify genetic variants associated with these traits. In the lab, you will help evaluate root growth under heat and drought conditions and develop mapping
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are derived from plant breeding, genomics, quantitative genetics, physiology, biotechnology, computational biology, and horticulture. You will be encouraged to establish robust collaborations with faculty