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will be determined based on factors including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $86,100 Aligning Machine Learning
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, biologics, and cannabis. Apply statistical and machine learning approaches (e.g., sequence analysis, latent class analysis, clustering) to examine medication use trajectories and patient subgroups
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machines that both learn from humans and help humans learn. The postdoctoral fellow will lead a project using AI technologies to support active learning in young children, by empowering them to create
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, score test measurements and questionnaires, and code data for computer entry. Perform quantitative review of forms, tests, and other measurements for completeness and accuracy. Extract data from source
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include, but are not limited to, using the latest computational learning-driven approaches, including computational social science, foundation models and multimodal machine learning, to enhance
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focuses on translational research at the intersection of bioelectronics, healthcare-focused nanofabrication, and emerging applications of machine learning in radiology. Our team operates within a state-of
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scientific research on computational linguistics, machine learning, practical applications of human language technology, and interdisciplinary work in computational social science and cognitive science. The
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. Research Themes and Projects: We are an interdisciplinary research team integrating single-cell and spatial genomics, lineage tracing, synaptic proteomics, functional perturbation screening, and machine
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clinical shadowing experiences. Research topics range from machine learning, designing, and evaluating clinical decision support content to disintermediate scarce medical consultation resources, evaluating
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and machine learning based software to assist clinical workflow and pre-clinical studies. Recent software developed from the group has been adopted in the clinic and preclinic labs. The scientific