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We are seeking to appoint a Research Fellow in Medical Statistics. You will join an innovative University that is passionate about inspiring people to learn and achieve, that celebrates
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-based, policy-relevant epidemiological, interventional research and longer-term modelling. We seek highly motivated individuals with a PhD or equivalent in data science, applied statistics, geography
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, health data science, health economics, psychology, health service research, computer science, signal processing, mathematics and/or statistics), with an excellent working knowledge of research methods in
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experienced people. You will have a PhD in a relevant area (e.g. epidemiology, economics, geography, public health, psychology, data science, applied statistics), with an excellent working knowledge of research
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degree (or be close to completion) in, for example, econometrics, statistics, or computer science, with experience of analysing large datasets. The post offers the opportunity to contribute to a research
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ocean warms. Biogeochemical-ecosystem models are currently used for this purpose but have difficulty scaling to the many thousands of plankton types. Statistical models do not have this issue and can be
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with a diverse training background to apply e.g. epidemiology, statistics, mathematics, engineering, physics, where you can apply your knowledge to health care data. You will have a PhD in epidemiology
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with a diverse training background to apply e.g. epidemiology, statistics, mathematics, engineering, physics, where you can apply your knowledge to health care data. You will have a PhD in epidemiology
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relevant methods are population dynamics theory (e.g. integrodifferential equation models or point process models) and Bayesian statistical methods (customising routines rather than simply using Bayesian
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independently once appropriate guidance has been provided. A PhD in biological science, computer science or statistics and/or relevant experience is required. This post is available immediately for 12 months in