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Assistant to join the Unit for Medical Statistics (UMS) in the School of Life Course & Population Sciences. The postholder will contribute to the work undertaken by existing staff and take day-to-day
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include experience in scientific programming and data computing, signal processing, statistical analysis. Knowledge of mathematical methods and numerical analysis are an asset. The candidate will be asked
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the UK. Activities will include: data preparation, statistical/epidemiological analysis, interpretation and dissemination. You should have post-graduate training and/or significant work experience in
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related field together with experience in biostatistics and/or health data sciences. Experience in programming statistical analyses, preferably in R and experience in writing scientific documents, e.g
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, excellent organisational and interpersonal skills, good understanding of computers and software, knowledge of statistics and experimental design, and be experienced in the use of statistical packages such as
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migrants in Wales, without Welsh or English as a first language. The research will incorporate a mixed-methods approach. This may include a quantitative approach (i.e. statistical data analysis) and a
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with internal and external collaborators. The post-holder should have a relevant MSc in the field of epidemiology, medical statistics, health data science or a related subject. Relevant experience
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with internal and external collaborators. The post-holder should have a relevant MSc in the field of epidemiology, medical statistics, health data science or a related subject. Relevant experience
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DPhil Studentship in Experimental Soft Matter (Fluctuations in microfluidic and nanofluidic systems)
physical chemistry, particularly soft matter chemistry/physics and statistical mechanics. Applicants should have, or be expecting to obtain, a first or upper second-class Masters honours degree in chemistry
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migrants in Wales, without Welsh or English as a first language. The research will incorporate a mixed-methods approach. This may include a quantitative approach (i.e. statistical data analysis) and a