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biomedical data science. Specific areas of interest include expertise in: •Clinical decision support and electronic health record data science •Machine learning and AI in health care, including design
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record of peer-reviewed publications Experience developing software with Python, R, and/or Julia Experience with machine learning and AI algorithms and tooling (e.g. PyTorch) Experience with remote
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of small-molecule drugs, nanomaterials/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning
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of small-molecule drugs, nanomaterials/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning
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with expertise in Machine Information Systems, time series, and forecasting. Preferred Qualifications Equipment Utilized Physical Demands and Work Environment Overview The MSIS department offers
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genotypes from sequencing data and downstream analysis of antigen presentation potential and immune-related features. Development of machine learning approaches for complex datasets: Design and