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research experience. Proven track-record analysing large-scale ‘omics and/or healthcare datasets, preferably in cancer genomics. Experience of advanced coding in Python or R plus Shell scripting; familiarity
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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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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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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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analysis skills (STATA or R) with high attention to detail Excellent written and communication skills for publications and policy engagement Ability to work independently and collaboratively across
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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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programming skills are UNIX/LINUX, and programming languages such as Python, R or MATLAB. Role Summary Implement and test different ML architectures for postprocessing precipitation forecasts over India