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Bayesian meta-analyses. This position also provides opportunities to develop innovative statistical methods related to clinical trial design, variable selection in high-dimensional data, prediction
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evaluation of machine learning, computer vision, and other algorithms, primarily in the context of health. They will be part of the thriving research community of Duke Spark (spark.duke.edu) where AI
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application to quantum theory and information science. Other application areas of interest include robust parameter estimation and performance bounds under model misspecification, integrated sensing and
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Calibration, Validation, and Uncertainty Quantification: The Postdoctoral Associate will develop and implement approaches for parameter estimation, calibration, validation, sensitivity analysis, and uncertainty
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Qualifications at this Level Education/Training: PhD (theoretical nuclear/high-energy physics, quantum information science, lattice gauge theories, quantum many-body dynamics) Experience: Preferred--computational