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biology Experience in machine learning and artificial intelligence Experience with genetics and genomic data Experience with large, diverse datasets and data mining approaches Proficiency in Linux and
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about the most recent advances in machine learning and data management in agricultural research. The participant will have the opportunity to collaborate with multiple USDA ARS scientists on using machine
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to viral sequence data. Exposure to machine learning or artificial intelligence methods, particularly as applied to genomics or infectious disease data. Experience in next-generation sequencing (NGS) data
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skills: Experience processing and analyzing diverse geospatial environmental data products. Experience developing, testing, and refining machine learning models. Experience developing HPC workflows
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competitiveness and excellence of our agriculture. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence. The SCINet/Big Data Research Participation
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should I apply? As an Oak Ridge Institute for Science and Education (ORISE) participant, you will join and learn from a community of scientists and researchers; and under the guidance of a mentor you will
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and platforms. This mentorship opportunity thus offers research training in applied plant breeding techniques as well as genetic and statistical analysis of collected data. Learning Objectives: As an
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): Chemistry and Materials Sciences (12 ) Communications and Graphics Design (6 ) Computer, Information, and Data Sciences (17 ) Earth and Geosciences (21 ) Engineering (29 ) Environmental and Marine
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institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and
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institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences, and