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approaches. With a focus on integrating large-scale data from genomics, transcriptomics, metabolomics, and proteomics, the Center collaborates across clinical, computational, and basic science domains
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operational skills - Management of (spatial) big data (quality, metadata, interoperability). - Interdisciplinary work (geographers, entomologists, epidemiologists, computer scientists, public health actors
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with staff ID card For more details, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards Must be authorized to work in the United States on
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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projections. Demonstrated experience in working with large data sets. Strong programming skills (e.g. Python, R) and ideally experience in high-performance computing. Demonstrated ability to work in a team
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applicants to apply. For additional information please see the Non-Discrimination Statement at the following web address: http://uhr.rutgers.edu/non-discrimination-statement
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Collaborative, and the Hopkins Business of Health Initiative to manage, analyze, and interpret large healthcare datasets, including Medicaid, Medicare, commercial, and all-payer claims. We are seeking a Sr. Data
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of the project, including data integration, association analyses (EWAS), and development of predictive models using large, multi-dimensional datasets. The postdoc will work closely with PRI researchers and
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towards innovative/integrated solutions. Responsible for full life cycle of medium to large sized complex projects; strong technical skills; strong ability to understand complex business processes. Complex
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impact, aiming to be ranked among the top engineering faculties worldwide. For more information, visit the Faculty website: https://www.unsw.edu.au/engineering/about-us Skills and Experience: Relevant