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, involved in study set up, trial management, and data analysis. The data analysis component will be primarily of genomic data. The purpose of this post is to identify and investigate genotype-phenotype
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of patients with inflammatory arthritis linked to detailed pathobiological data since 2008, paving the road for precision medicine trials in inflammatory arthritis. More information can be found on our website
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regression models to complex forms of observational data, and of applying causal inference approaches to health data are essential. Experience of analysing time-to-event outcomes is desirable. This role offers
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Stanford whose work is relevant to your proposed project is desirable. Please note applications without this will not be considered. Please quote reference EPH-DPH-2025-07 or for more information contact
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computational research projects and data infrastructure carried out in the research group. The post-holder will be able to develop research questions within Statistics, Population Data Science, Computational
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and contribute to methodological and applied projects in risk prediction using electronic health records data. There is increasing interest in blending concepts of causality into risk prediction models
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proven ability using statistical software for managing and analysing data using STATA/SAS/R. Further particulars are included in the job description. The post is full-time 35 hours per week, 1.0 FTE and
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of the selection criteria. Please provide one or more paragraphs addressing each criterion. The supporting statement is an essential part of the selection process and thus a failure to provide this information will
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specialties and disciplines with a key interest in cancer MDT work. Experience in quality improvement, project management, data collection and analysis would be advantageous. A demonstrated ability to
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for observational research. The successful candidate will be part of Discipline 1 (Surveillance, Epidemiology, Electronic Health Records Research, Big Data). The post-holder will have a postgraduate degree, ideally a