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clinicians and are part of a professional nursing community that is actively involved in transforming health and inspiring hope for all Virginians and beyond. he Internal Traveler Program is an opportunity
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for data analysis and research. Machine Learning Skills: Experience with machine learning algorithms, transformers, or large language models to analyze genomic data. Computational Proficiency: Skilled in R
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clinicians and are part of a professional nursing community that is actively involved in transforming health and inspiring hope for all Virginians and beyond. Varies by assignment The Internal Traveler Program
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regulatory clearance of a new AP System (that included the algorithm program developed at the Center), published on October 16, 2019 in the New England Journal of Medicine . For more information visit: https
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Supervisor will adhere to prescribed algorithms and guidelines for making staffing decisions. As Incident Commander for Emergency Management the SRO Nursing Supervisor will coordinate the dissemination
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. For questions regarding this position, please contact Prof. Rebecca Pompano, Ph.D., at PompanoGroup@virginia.edu . For questions about the application process, please contact Rich Haverstrom, Faculty Search
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processing to work on research in personalized behavioral health. The successful applicant will collaborate with an interdisciplinary team to develop software and computational models that leverage data from
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assists in experiments for the Infectious Diseases Division the laboratory of Prof. Steven Zeichner, MD, PhD. The goal of the lab is to study infectious disease pathogenesis and work to develop new
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prevalence data collection, evidence-based policies, procedures, and protocols, and advisement of appropriate support surfaces, products, and staff decision-making algorithms. • Provides consultation and
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instruction as it pertains to research, genetic, or various other medical processes as required or assigned. Performs a variety of administrative tasks, training, and education within the Health System