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excellent knowledge of advanced statistical methods and experience in analysing large-scale datasets, as well as solid practical experience in the use of STATA, R or a similar software package, and good
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of Survey Methodology. You will also have excellent knowledge of advanced statistical methods and experience in analysing large-scale datasets, as well as solid practical experience in the use of STATA, R
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following skills and experience: Essential criteria PhD qualified in relevant subject area Experience working with large datasets e.g. CPRD or similar Experience with relevant statistical software (STATA or R
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steer institutional or funder priorities. Clarify your precise contribution and any demonstrable impact (e.g. citation in a funding call, adoption by an R&D organisation, reference in parliamentary
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written and verbal communication skills, experience with developing and implementing Bayesian statistical models, and be proficient in computer programming in e.g. R or Python, and C/C++. Please ensure you
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relevant subject area Experience working with large datasets e.g. CPRD or similar Experience with relevant statistical software (STATA or R) Research experience in Public Health/Epidemiology/Informatics
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(or capacity to develop understanding) in relevant field Good programming skills in a data processing and visualization language such as Python, MATLAB, R or NCL Experience with UNIX/LINUX and High
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tools such as R, Python, or MATLAB as well as relevant machine learning frameworks Experience in statistical data analysis, and expertise in areas such as experimental design, linear/nonlinear models
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mathematics e.g. calculus and probability Ideally experience with command line and sequence analysis Good programming skills (e.g. R, Python, C/C++) Knowledge of basic statistics and application in R or similar
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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