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the soil-water-plant-air continuum using process-based models. You will learn how to take proper soil, plant and air samples that influence carbon and nitrogen dynamics and learns how soil and plant
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predictive modeling, to identify distinct phenotypes of diabetes and characterize factors associated with disease onset, progression, complications, and mortality. Gain experience analyzing administrative
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. The vision of the agency is to provide global leadership in agricultural discoveries through scientific excellence. ARS’s SCINet/Artificial Intelligence (AI) Center of Excellence Research Participation Program
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Implementing Bayesian networks and uncertainty quantification techniques to account for sensor noise and model confidence limits Designing, training, and fine-tuning computer vision models to extract clinically
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of the research project, research may also incorporate advanced optical diagnostics, quantitative image analysis, computational modeling, and remote sensing technologies to improve understanding, evaluation, and
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underlying genetic components, helping researchers better understand how plant genetics and fiber quality interact. You will engage in a collaborative, multidisciplinary research program spanning chemistry
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collecting soil, plant, and water samples; monitoring soil moisture with advanced sensors; organizing and processing research data; and contributing to modeling efforts that examine water and nutrient dynamics
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security threats. The CDC IPP regulates the importation of infectious biological materials that could cause disease in humans to prevent their introduction and spread into the U.S. The program ensures
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Must be a U.S. Citizen Preferred Skills: Experience with MATLAB Familiarity with emerging technologies including instrumentation, computer modeling & simulation (e.g. Matlab, CFD, and/or other), and the
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join a community of scientists and researchers in an effort to research modeling approaches related to neural stimulation and inhibition by laser exposure. Research will primarily focus on