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research or industry experience will also be considered. Good statistical and analytical skills are necessary, ideally with the ability to work in R and experience with bioinformatic tools/software. Coding
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model fitting, including Bayesian model fitting, is desirable but not essential. Familiarity or experience of management and analysis of large multidimensional real world data sets using Stata, R, Python
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research or industry experience will also be considered. Good statistical and analytical skills are necessary, ideally with the ability to work in R and experience with bioinformatic tools/software. Coding
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sufficient specialist knowledge in transcriptomics and NGS sequencing as well as the essential computational skills (R, Unix or Python) to develop research programmes in this area, and familiarity with
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package such as Stata/R. A commitment to multi-disciplinary and collaborative working is also essential. The ideal candidate would have experience using electronic health records for pharmacoepidemiologic
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set-up, and data collection and analysis. - Have the ability to analyse and interpret data using appropriate statistical packages (e.g., conducting linear mixed effects models in R). - Have experience
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package such as Stata/R. A commitment to multi-disciplinary and collaborative working is also essential. The ideal candidate would have experience using electronic health records for pharmacoepidemiologic
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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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Demonstrate proficiency in R/BioConductor and High Level (e.g. python) programming languages, Databases (SQL), development and maintaining code repositories (version control) Ability to assess resource
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programming skills in languages such as Python, MATLAB or R. Familiarity with UNIX/LINUX. High level analytical capability. Ability to communicate complex information clearly. Ability to assess resource