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internationally recognized, with interests spanning a broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease
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the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships available in Digital Endocrinology in the Marie
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September 30, 2026. Your immediate leader will be the leader of the epidemiology and Medical Statistics group. Duties of the position Complete the doctoral education until obtaining a doctorate Carry out
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outcomes Synthetic data generation (virtual patients) Statistical model checking to ensure statistical correctness of the results Machine learning–based classification and regression methods The candidate
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, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling. The centre has numerous collaborations with leading biomedical research groups
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broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling
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quantitative analysis and statistical/econometric methods. Very good competence with statistical software (Stata, R, Python). Good written and oral English language skills. PLEASE NOTE: For detailed information
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) or the equivalent in Computer Science, Information Security, Statistics, or related fields at the time of application Special requirements for the position: possess solid programming skills (e.g., Python, R, GIT
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in the structured PhD programme at the Department of Mathematics & Statistics (https://www.reading.ac.uk/maths-and-stats/ ) About the project/work tasks: This position is part of: 19 PhD Fellowships
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been submitted. Application requirements We encourage applications from candidates who have solid quantitative skills and a strong background in fields/disciplines such as statistics, operations research