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Be You. At Duke, we celebrate individuality and the unique perspectives that each member of our community brings. As the Machine Learning Research Data Analyst, Ophthalmic Imaging, you'll play a
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information for at least three professional references. References will be contacted only at a later stage of the process. Occupational Summary The Marine Geospatial Ecology Lab (MGEL) at Duke University seeks
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leading experts in autism research, computer vision, machine learning, psychiatry, and developmental science to develop innovative technologies that improve how caregiver-child interactions and
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equation models for Epstein–Barr Virus (EBV) and HIV-1 infection dynamics in human lymphoid tissue. New mathematical models will be informed by longitudinal experimental data, including multiplexed spatial
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-Medicare, SEER-Medicaid, claims data, cancer registry data, and EHR-derived cohorts to advance cancer equity and improve outcomes for patients with head and neck cancer. Doctoral degree in Epidemiology
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participatory design and student co-creation to develop responsible approaches to multimodal data collection, research design, and dissemination. ● Design and deploy a platform for linking measures of AI use
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will help advance novel imaging technologies, analyze complex medical imaging data, and contribute to research that has the potential to improve patient outcomes worldwide. What You'll Do: Conduct
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on identifying and validating surrogate endpoints for overall survival using data from cancer clinical trials and patient registries, developing prognostic models of clinical outcomes in cancer, and conducting
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deep learning for CT image analysis and reconstruction Computational and digital-twin models for preclinical imaging Analysis of longitudinal and dynamic imaging data Development and validation
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will lead the execution of the experimental plan, work on the design of the data analysis methods, and perform the appropriate computational analyses. You will perform literature searches and use them