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economic studies funded by the UK National Institute for Health and Care Research. Experience of conducting economic evaluations using suitable statistical software (e.g. STATA, R or SAS) is essential
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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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Minimum Qualifications Candidates must have a PhD and proven research experience in computation analyses, statistics, mathematical modeling, or engineering. Prior experience in Ophthalmology research is not
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Parkinson’s Disease, or markers of brain structure and functioning, depending on the dataset. To do this, knowledge or willingness to be trained in advanced statistical modelling, ideally with an interest in
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examining the intersection of environmental challenges and the just transition. This role is ideal for candidates planning to apply to top PhD programmes and looking for hands-on research experience on high
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
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the decision analytic modelling field research field and contribute to high quality reports for funding bodies and peer-reviewed outputs. You will hold a DPhil/PhD in health economics or a related quantitative
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second PhD student focused on the development of bespoke probabilistic models. Thus, an affinity towards statistical modeling is important. In-depth skills in probabilistic modeling and hands-on experience
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to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record of applying ML in academic or industry
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specimens. Qualifications & Requirements Pursuing PhD degree in mechanical engineering, familiarity with metal 3D printing. BACKGROUND CHECKS/CLEARANCES Employment with the University will require successful