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-quality epidemiological research and statistical analyses using complex, large-scale health data. You will support study design and analysis, contribute to publications and funding proposals, provide
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-qualification research experience. Relevant areas of research include computational chemistry, structural biology/bioinformatics, statistics, machine learning, computer science or mathematics. They will have a
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Applications are invited for a Senior Medical Statistician, to join the Primary Care Clinical Trials Unit (PC-CTU) trial statistics team. The successful applicant will be expected to contribute
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computational, statistical and social data science approaches to expand knowledge on gender inequalities in digital connectivity, as well as the impacts of digital gender inequalities on social, demographic, and
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project that will enhance Population Health research in Oxford. Applicants should have an MSc in a subject relevant to Population Health (e.g. medical statistics, epidemiology, health economics, sociology
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activities, and adapting existing mathematical and statistical methods for analysis of high-dimensional imaging data, and developing new ones. Other responsibilities will include analysing quantitative imaging
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Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics (HES). Data from these and other sources on healthcare resource use, costs, and effectiveness measures including clinical and PROMs
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expertise in statistics, mathematics, engineering and AI with industry scientists. Within the partnership, small research teams will focus on ambitious, ‘blue sky’ research for novel methods development
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Postdoctoral Researcher Data Scientist. You will play an important role in the contribution of statistical analysis and new models of analysis of complex data sets. You will be responsible for providing analysis
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, computer science, statistics, or a related field together with strong programming skills in Python, R, or similar languages, and proficiency in high-performance computing. You will have experience in large-scale