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collaboration with the mentor and other project members, to refine the focus of these activities based on the knowledge base, skill sets, and interest of the participant. Learning Objectives: The fellow will be
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. The DBNRRC conducts nationally significant research to enhance the productivity, sustainability, and health benefits of U.S. rice production, and this fellowship is designed for a fellow interested in learning
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research applying artificial intelligence (AI) and machine learning (ML) techniques to analyze cervid movement patterns. GPS telemetry data obtained from free ranging cervids will be used by the participant
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reporting soil health results back to participating farmers. Learning Objectives: Under the guidance of a mentor, the fellow will gain hands-on experience with laboratory methods for soil health assessment
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results back to participating farmers. Learning Objectives: Under the guidance of a mentor, the fellow will gain hands-on experience with laboratory methods for soil health assessment, learn how to handle
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expected to learn both independently and collaboratively within a multidisciplinary research team, contribute to experimental design and data analysis, publish findings in peer-reviewed journals, and
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genomes. The primary project of the fellow will be to learn how to characterize sex-chromosomes in tephritid fruit fly species to contribute to functional genomic studies that will serve as a foundation for
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development, institution review board protocol(s), and data collection Learning about new domain(s) relevant to the Cognition and Modeling Branch at Wright-Patterson AFB Reporting research updates in individual
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, software applications, record keeping, compliance training, and the principles of scientific study design. Learning both general and specialized research skills that will support advancing your scientific
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conditions. Anticipated outcomes of the project include criteria for selection of fungal genotypes that will be developed into new biocontrol products for mitigation of crop aflatoxin contamination. Learning