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Interview Motivated in learning new methodologies and applying new knowledge Essential Interview Knowledge of the approximate Bayesian machine learning (e.g. MCMC) (assessed at: Application form/Interview
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Natural Language Processing, Applied Machine Learning, Neural Networks and Deep Learning as well as Machine Learning for AI and Data Science and Bayesian Theory and Data Analysis. We are looking
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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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health environment and 0 to 1 year of experience. Strong background in one or more areas of machine learning (Bayesian networks, neural networks, Markov Models, convolutional networks etc.) Exposure
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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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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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-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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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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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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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