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environment. Further information on the programme is available at: PROGRAMME | CREATE PhD Programme (create-phd.org) This programme is aimed at supporting health professionals who wish to undertake rigorous
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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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analysis. Experience analysing large data sets is also essential. Further particulars are included in the job description. The post is full-time 35 hours per week, 1.0 FTE and fixed-term until 29 February
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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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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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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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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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, 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