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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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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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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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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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validate algorithms for estimating heat stress, counting animals, and estimating mass in real-time. Although research is needed to integrate One Health assessments across the soil-pasture-animal continuum