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machine learning methods, including cluster analysis and predictive modeling, to identify distinct phenotypes of diabetes and characterize factors associated with disease onset, progression, complications
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technology or Artificial Intelligence (AI) tools to solve business or administrative problems, demonstrated knowledge with Machine Learning (ML) and AI tools. Strong integration experience in enterprise
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the shallow subsurface (<10 meters depth). Experience with soil moisture/salinity and sapflow sensors. Experience using neural networks and machine learning tools. Stipend $70,000.00 – $80,000.00 Yearly Point
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response to military relevant stressors, and in identifying nutritional countermeasures. Various methods including molecular assay techniques (e.g. qPCR, ELISA, confocal microscopy, -omics, immunoblots
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-and-mouth disease, classical swine fever, and African swine fever. Research Project: FADRU has opportunities for post-graduate research scientists interested in training fellowships conducting research
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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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of the agency is to provide global leadership in agricultural discoveries through scientific excellence. Research Project: This Post-Doctoral Fellowship opportunity will take place at the USDA Agricultural
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? Under the guidance of a mentor, you will engage in activities and research that will expanding your learning in several areas. These include, but are not limited to: Fabricating new plasmonic (gold
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nucleic acid extractions, amplicon sequencing, data management and analysis. You will learn how to identify risks and improvement opportunities, ensure compliance with established policies and agency
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the guidance of your mentor, you will study Fusarium Head Blight (FHB), one of the most significant diseases affecting wheat production, grain quality, and food safety worldwide. You will learn how