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-Resistant Organism Repository and Surveillance Network (MRSN) is a unique entity that serves as the primary surveillance organization for antibiotic-resistant bacteria across the Military Health System (MHS
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to the military research network (e.g., Defense Health Agency, Army Futures Command). Why should I apply? Under the guidance of a mentor, you will gain hands-on experience to complement your education and support
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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 artificial intelligence (AI) and machine learning, to help
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, leading to peer-reviewed publications. The fellow may also have the opportunity to be included in helping with the USDA new world screwworm response. Learning Objectives: The fellow will learn techniques in
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machine learning algorithms for various research projects creating medical image automation algorithms writing combat casualty care relevant military research proposals preparing manuscripts for submission
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improve federal transit operations and oversight. Projects may include: Performing exploratory data analysis across diverse FTA datasets. Building and evaluating statistical and machine learning models
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wildland–urban interface zones along the U.S. West Coast. Under the guidance of a mentor, you will study and implement an ensemble machine-learning framework to enhance debris flow probability prediction
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professional goals. Along the way, you will engage in activities and research in several areas. These include, but are not limited to: Learning all aspects of current research including laboratory protocols
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aided design (CAD), computer aided manufacturing (CAM), manipulation of digital manufacturing software tools, 3D object slicers, support structure optimizers, computer programmings, and scripting
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statistical software. Learning Objectives: Learn about the implementation of the application of machine learning methodologies in plant phenotyping and genotyping for the sugarcane molecular biology lab. Learn