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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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, development, implementation, and coordination of research and laboratory protocols to investigate transmission of enteric pathogens in low-income households of Salvador, Brazil within the context of large-scale
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relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning techniques, and
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data integration for epidemiological innovation, funded by the Wellcome Trust. The CONNECT project offers the opportunity to work with the largest population-based UK cohorts, such as UK Biobank, CPRD
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for a team player with exceptional communication skills who is enthusiastic about developing cutting-edge cardiotherapies whilst also supporting undergraduate and postgraduate student learning through
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large health datasets on topics including pharmacoepidemiology and non-communicable diseases. The post requires strong data management and quantitative skills with expertise in a common statistical
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, relevant experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, strong quantitative skills
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for cardiovascular disease in this patient group using linked electronic health record data. The post offers an excellent opportunity to develop expertise in risk prediction methodology for electronic health records
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of a large multidisciplinary collaboration between LSHTM and Oxford Brookes University (lead partner), UCL, LSE, University of Leeds, University of Edinburgh, and a wide network of UK stakeholders
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to important public health topics. Studies will include descriptive epidemiology and use emulated target trial approaches for robust causal inference within large national health datasets. The post offers