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and reduction Development and application of big data analytics for large X-ray data sets Application of Bayesian methods to X-ray data Combinatorial analysis of various data from complementary
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. Experience leading investigations linking simulations to observational data. Experience with statistical characterization of data, preferably within a Bayesian framework. Job Description: A Post-doctoral
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model. The post holder will take the lead in developing and testing Bayesian joint models for relating height and body composition growth features to early life exposures and later outcomes. They will use
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(e.g., REDCap). Conducts complex statistical analyses on observational studies and clinical trials, applying techniques including regression models, multiple imputation, nonparametric methods, Bayesian
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-dimensional statistics, semiparametric/nonparametric methods, and Bayesian statistics. The teaching duties will be assigned by the Head of Department with a reduced teaching load in the first year of
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patients by estimating the systemic exposure to the drugs from the population models combined with drug measurements using Maximum a Posteriori (MAP) Bayesian estimations. The work is to lead to several
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of rail with wider city and regional transport networks. A focus of this work is the application of optimisation techniques (e.g. evolutionary algorithms, or Bayesian techniques) to identify high performing
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and Bayesian Theory and Data Analysis. We are looking for an associate able collectively to cover the different modules on the programmes, mainly around AI and Data Science, as well as supporting others
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clinical trials to assess its ability to measure hydration state. This project would use data from WearOptimo’s hydration sensor and develop novel Bayesian methods to model hydration state. How can hydration
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effects model. What will you be doing? The post holder will take the lead in developing and testing Bayesian joint models for relating height and body composition growth features to early life exposures and