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the unique opportunity to develop skills in analytical, statistical and data science techniques, working with real world data to provide recommendations for UKHSA on how pharmacy OTC data could be used
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responsibilities of the job - Access and analyse national cancer registration data, population statistics, and mortality data by ethnicity. - Calculate ethnicity-specific absolute risk thresholds and estimate
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support to develop their research career beyond completion of doctoral studies. Applicants should have a primary degree in a relevant methodological discipline (such as statistics, health economics) or a
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/sociology/biology/environmental sciences/microbiology/statistics/veterinary or human medicine). Applicants whose first language is not English require an IELTS score of 6.5 overall with a minimum of 5.5 in
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replacement, statistics and working with joint registry data. You will be based in the Integrative Musculoskeletal Biomechanics (IMSB) research group and join a thriving PhD research community in the School
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are looking for highly motivated candidates with: A strong academic background in computer science, AI/ML, bioinformatics, or related fields such as mathematics and statistics Experience or strong interest in
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FTE, 30 hours per week minimum) and is fixed term up to 31/03/2027. About You You will have extensive expertise in statistics, likely including a PhD, and experience and interest in working in
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duties will include contributing to the provision of statistics, research methodology, and laboratory classes to year one and year two undergraduates, in addition to a number of designated administrative
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, applied statistics, biomedical sciences, health services research, or a medical degree with relevant experience, or equivalent professional experience. Demonstrated proficiency in quantitative methods and
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Responsibilities for the role include: Data collection, cleaning, and merging from large-scale microdata sources (e.g., patents, dissertations, bibliometrics). Conduct data analysis using econometric and statistical