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We are looking for a postdoctoral researcher to develop and implement tools for analysis of output from Bayesian inference under phylogenetic models About the position A postdoctoral researcher
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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Correct), Bayesian statistics, systems theory and artificial intelligence are to be used as a basis in order to explore and implement a continuous calculation chain starting from observable and controllable
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high
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simulations of reactor core, and other system components Develop reduced-order calibration approaches and apply machine learning and Bayesian calibration methods to enable multi-scale, multi-physics model
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references. If you advance to the final stage of the application process, references will be contacted via automated email, which may be filtered into spam or junk folders. We recommend informing your
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rate standardization, stock assessment models, and statistical modeling in both frequentist and Bayesian frameworks • A solid track record of publications Salary Information Commensuate with experience
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Arctic locations- Knowledge of spatial analysis and Bayesian statistics - Previous experience conducting fieldwork in northern ecosystems - Experience working with drone imagery and drone piloting Offer
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experience in developing models to analyze temporal data. Prior experience in utilizing Bayesian modeling in related applications. Required Application Materials: CV Contact information for reference letters
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Titan Krios microscope equipped with a Gatan KIII-Biocontinuum Direct electron detector/energy filter combination. The Hormel Institute also houses an equipment core including fluorescent microscopes as