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Field
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, mathematical psychology (computational modelling) and/or human factors methods and related statistical techniques (including Bayesian hierarchical methods) Experience with the development and application
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, data mining, Bayesian methods, and statistical learning About Working at the Crick Our values We are bold. We make space for creative, dynamic and imaginative ideas and approaches. We’re not afraid to do
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modelling of climate-sensitive infectious diseases, with a particular emphasis on Bayesian hierarchical modeling using Integrated Nested Laplace Approximation (INLA). The work will contribute to ongoing
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more novel problems. Keywords include: automatic experimental design, Bayesian inference, human-in-the-loop learning, machine teaching, privacy-preserving learning, reinforcement learning, inverse
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interpreted very broadly, e.g.: topics in Bayesian Inference and Robotics; ‘Science’ covers any typical topic in Natural Science and Engineering (Epidemiology, Biology and basic science in biomedicine
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or a numerate discipline OR equivalent experience. Broad knowledge of probabilistic models, Bayesian inference and machine learning methods. Good knowledge of R, Python or both (links to project source
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, they will have prior knowledge of infectious disease modelling, Bayesian inference methods and optimisation methods. They will have a developing research profile, with a demonstrated ability to publish
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Candidate We seek an ambitious researcher with a strong foundation in Bayesian theory, machine learning, and mathematical modelling. You should be confident in software development and capable of passing a
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.: topics in Bayesian Inference and Robotics; ‘Science’ covers any typical topic in Natural Science and Engineering (Epidemiology, Biology and basic science in biomedicine are included but clinical medical
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.: topics in Bayesian Inference and Robotics; ‘Science’ covers any typical topic in Natural Science and Engineering (Epidemiology, Biology and basic science in biomedicine are included but clinical medical