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the Methodologies Used to Incorporate Non-randomised Evidence in Healthcare Decision-making” project (Chief Investigator: Prof. Kate Ren ) aims to develop innovative statistical and causal inference methodologies
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. To achieve these objectives, the fellow will work with taskforce members to: Develop recommendations for best practices and guidelines for responsible data collection and analysis Engage stakeholders
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responsibilities Research: Contribute to or lead on the statistical aspects of the development of high quality research bids to evaluate the effectiveness of new health technologies, which is recognised both
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opportunity for the successful applicant to develop further towards leading an independent academic career at the interface of AI and engineering applications (such as advanced manufacturing). The role holder
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, on-site medical cover for high risk studies, and assessment of, reporting and acute management of potential adverse events Attend meetings related to the development and conduct of EM studies as agreed with
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Total Reward Package includes a competitive salary, a generous Pension Scheme and annual leave entitlement, as well as access to a range of learning and development courses to support your personal and
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, disseminate research findings through peer-reviewed publications and academic conferences, and engage with policy, practice stakeholders, and the public. You will also have the opportunity to develop your own
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with a view to developing new diagnostics and vaccines. Main duties and responsibilities Provide medical assistance to CRF staff in delivery of EM study portfolio, as directed by CRF Director, and/or by