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publications Desirable Familiarity with containerisation (e.g., Docker or Singularity) of informatic pipelines/workflows Experience in multiple omics methodologies Understanding of the application of statistical
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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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, statistical and data science techniques, working with real world data to provide recommendations for UKHSA on how pharmacy OTC data could be used for surveillance in the future. The project will be supported by
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techniques that are useful for the modelling of many real-life systems. These include the development and analysis of stochastic models, computer simulations, differential equations, statistical inference
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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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statistical methods. Good interpersonal and communication skills Problem solving skills For applicants who are non-native speakers of English, the University requires IELTS of 7.0 (with no band less than 6.5
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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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of the underlying the physical processes leading to predictability and forecast skill of North Atlantic cyclones. The project will also explore statistical post-processing methods to see if raw forecast skill can be
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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