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modeling, economic evaluation, and surveillance to enhance analytical tools. Activities will focus on gaining hands-on experience and contributing to emergency preparedness and surveillance planning
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of microphysiological systems or organ on a chip model for viral agents. Research project emphasis is placed on determining virus growth and stimulation of an appropriate immune response that mimics what is observed in
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condition leading to medical discharge following combat related trauma in our military. Learning opportunities include, but are not limited to: exposure to various aspects of pre-clinical research by
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machine learning, coupled fire behavior/fire atmosphere modeling, air quality modeling, and system evaluation. Depending on their skills and interests, they can participate in various aspects of the project
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. Qualifications The ideal candidate should have a strong background in the mathematical and computational aspects of modeling subsurface and surface flows. Knowledge in machine learning, data assimilation, and
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of the project is to provide a timely update and modifications of this model, as new science and methods have evolved since its development. Learning Objectives: The selected fellow in this project will have the
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language models Familiarity with structured and unstructured database management systems Knowledge of AWS cloud services and data integration using APIs Knowledge of supervised machine learning tools
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. Along the way, you will engage in activities and research in several areas. Learning activities will focus on: The development and characterization of animal models and/or microphysiological systems
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countermeasures targeting hantaviruses. Currently we use Syrian hamsters as models of hantavirus pulmonary syndrome (HPS), a disease with a very high case-fatality rate in humans. Andes virus is the hantavirus