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collects physiologic and biologic data in extreme environments and utilizes this data to develop novel prediction algorithms of acute mountain sickness, heat exhaustion, cold injury, and other environmental
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). The project aims to 1) assess the performance of existing Medical Dictionary for Regulatory Activities (MedDRA)-based search algorithms compared to a novel algorithm that leverages other features (e.g., patient
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to join this development team as a fellow and learn to create, evaluate, and validate rapid, accurate, and sensitive diagnostic methods for detecting disease pathogens. The fellow will have an opportunity
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development. You will gain experience researching advanced in silico prediction algorithms, analyzing machine learning approaches for toxicity pattern recognition, and participating in developing standardized
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offering a graduate research fellowship at the Combat Capabilities Development Command – Chemical Biological Center (DEVCOM-CBC). As a research fellow, you will join a community of scientists to support our
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pursues disruptive qubit research, innovative workforce development programs, and deep, collaborative partnerships to tackle some of the hardest open problems in quantum information science and technology
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epidemiologic patterns as swine IAV is transmitted among hosts and across landscapes will be quantified. The participant may also have the opportunity to be involved in the development of novel algorithms
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. The participant may also have the opportunity to be involved with the development of novel algorithms, bioinformatic tools or analytical pipelines that quantify the diversity of RNA viruses that may be deployed in
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data have the potential to rapidly check animals and serve as a tool for farmers, ranchers, and researchers. Current research is being done by PI to automate imaging and spectral data to develop and