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exciting project that will develop new approaches to handle missing data in statistical analyses based on machine learning methods. The Research Fellow will be based in the Department of Medical Statistics
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project developing Bayesian causal inference methods for mediation analysis using Electronic Health Records (EHR) data. The Research Fellow will design and implement Bayesian methods and software
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Development opportunities Pension Scheme with generous employer contribution Various schemes including Cycle to Work, Season Ticket Loans and help with the cost of Eyesight testing. Free parking The successful
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analysis to join a dynamic team that has, for the past 8 years, developed an extensive body of research on corruption, governance and anti-corruption strategies. In the Accountability in Action project
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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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documentation, supporting partners in protocol development and laboratory set up and training before and during the clinical trials. The post-holder will also be expected to contribute to ad-hoc activities
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vaccination barriers and facilitators, develop forecasts of vaccine coverage for existing and novel vaccines (e.g. HPV, RSV, malaria), and support the design and implementation of small area estimation and
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, and OpenSAFELY, and to develop and apply the new generation of analytical methods to study environmental health risks and climate change. The post will provide opportunities for interactions with
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range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment policies, flexible working arrangements, and
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develop research that can inform policy in this important area. The candidate should have a background in a quantitative subject, in particular epidemiology or medical statistics and be familiar with