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Field
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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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or higher and two (2) years of data science or analytics experience or education and work experience to equal six years. Experience with Bayesian statistics and censored datasets preferred. Background
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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
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the impact of social, environmental, and household factors on population health by integrating administrative data from various sources. What we are looking for Experience of Bayesian inference in a
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probability, likelihoods and Bayesian analysis. We are also seeking individuals with a strong interest in public health. Key Responsibilities: Develop models that integrate different data types (e.g., serology
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probability, likelihoods and Bayesian analysis. We are also seeking individuals with a strong interest in public health. Key Responsibilities: Develop models that integrate different data types (e.g., serology
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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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Physics and Number Theory. More broadly, the School also has research strengths in Bayesian and Monte Carlo Methods, Biomathematics, Biostatistics and Ecology, Computational Mathematics, Data Science
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background in developing and integrating probabilistic graphical models, Bayesian networks, causal inference, Markov random fields, hidden Markov models, high-dimensional probability, stochastic modeling, and
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, and visualization are preferred. Prior training in longitudinal data analysis, survival analysis, Bayesian methods, and joint modeling is highly desirable. Experience working with clinical or biomedical