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being a defining ethos. You will be part of the Health Inequalities Policy Research (HIPR) Group, in the Department of Public Health, Policy and Systems at the University of Liverpool. The HIPR vision is
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We have an exciting opportunity for a Health Data Scientist/quantitative Epidemiologist to join the University of Liverpool Veterinary Data Science group. We combine large data sets primarily from
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We are seeking to recruit a Senior Enterprise Manager (Science & Engineering) - to join our increasingly successful Enterprise Team. The role will be central to the successful delivery of the commercialisation of University IP assets arising primarily from research activities in the Faculty of...
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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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The University of Liverpool Management School is seeking to appoint a Postdoctoral Research Fellow. The post holder will undertake quantitative analysis as part of a research programme which
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The University of Liverpool Management School is seeking to appoint a Postdoctoral Research Fellow. The post holder will undertake quantitative analysis as part of a research programme which
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of results of clinical trials within the portfolio of research of the Liverpool Clinical Trials Centre (LCTC). Under the supervision of a Statistical Lead you will work across a diverse range of clinical
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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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ethos. You will be part of the Health Inequalities Policy Research (HIPR) Group, in the Department of Public Health, Policy and Systems at the University of Liverpool. The HIPR vision is to improve
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at the University of Liverpool, and will benefit from our adjacent Centre for Computational Biology. About you You will have a proven ability to develop innovative theoretical and/or computational methods. The most