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Postdoctoral Fellow with Professor Samuel Kou. Professor Kou’s group focuses on research in statistical modeling and stochastic inference in protein folding, biology, chemistry and medicine, Bayesian inference
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(publications, preprints, software, reports). Highly desirable: • Demonstrated experience in inverse problems and/or statistical inference (ideally Bayesian). • Prior experience with satellite remote
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high information content Flow MRI datasets with physics based modelling and Bayesian inference to determine constitutive models for non-Newtonian and other complex fluids in situ. The project will
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statistics, Bayesian statistics, burden mapping, measuring the impact of the environment on disease among others. The PI has projects in both infectious and chronic disease, measuring the impact of
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of Epidemiology, and will be a member of the HIV Inference Group a geographically distributed and substantively diverse research team led by Dr. Jeff Imai-Eaton. Postholders will be responsible for leading and
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the mismodeling of gravitational waves, of astrophysical environments, or of noise artifacts in gravitational-wave inference, The development of Bayesian data analysis techniques to carry out parameter estimation
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. The postholder will be based in the Center for Communicable Disease Dynamics within the Department of Epidemiology, and will be a member of the HIV Inference Group a geographically distributed and substantively
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and genomic) data to address the most pressing health research challenges. The advanced analytics team specialise in the development and application of statistical methodology (including Bayesian
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, cross-spectra, filtering, mode fitting). Inverse problems / inference applied to astrophysical flows (e.g., inversion methods, Bayesian/statistical inference, uncertainty quantification) Strong
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, New York 14850, United States of America [map ] Subject Areas: Data Science / Statistics , Applied Mathematics , Artificial Intelligence , Bayesian Statistics , Big Data , Scientific Machine Learning