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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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, Bayesian statistics) - Remote sensing theory (e.g., radiative transfer physics; algorithm development) - Remote sensing measurements and instrumentation, including calibration and validation, experience
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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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opportunity to learn about zoonotic diseases, their impact on trade, learn surveillance procedures, diagnostic testing methodologies and algorithms, whole genome sequencing, and molecular epidemiology. Mentor(s
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Aeromedical Evacuation (AE) medical crews. The goal of the project is to embed interactive software algorithms, derived from Aeromedical Evacuation Clinical Protocols (AECPs), directly into the provider's
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be focused on learning how to develop algorithms, performing biochar characterization tests, and characterizing microbial communities that colonize biochar in different ecosystems. Learning Objectives
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areas. These include, but are not limited to: Applying machine learning algorithms to solve real-world problems. Creating and structuring databases for storage, retrieval, and image analysis. Determining
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applications and methods Gaining experience with Qubit coupling schemes including hetero – qubit ensembles Designing Qubit cross – talk mitigation techniques Applying Quantum algorithms for small to medium scale
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to participate and gain knowledge in researching existing topography, wave, water level, ecological, and sediment transport data from the laboratory and/or field to validate existing models and test algorithm
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be focused on learning how to develop algorithms, performing biochar characterization tests, and characterizing microbial communities that colonize biochar in different ecosystems. Learning Objectives