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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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Salvador, Brazil. The post-holder will also contribute to the laboratory analysis, data cleaning and management, and data analysis and write-up a study to assess environmental exposures to enteric pathogen
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access to cutting-edge technology across the UK healthcare and biotech sectors. Read more about the initiative here This is a unique opportunity to help build a first-of-its-kind cancer AI development
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to achieve a higher degree during the fellowship (e.g. PhD) and will need to have excellent academic and organizational skills, ideally with previous experience of data analysis and/or genetics. About the
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degree, ideally a PhD, in health economics, medical statistics, data science, epidemiology or a related field. A clear conceptual understanding of causal inference methods such as instrumental variable
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Right to work: Applications from job seekers who require sponsorship to work in the UK are welcome and will be considered alongside all other applications. For further information visit the UK Visas
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, Professors Ruth Keogh and Kate Walker. Applicants should have a postgraduate degree, ideally a PhD, in medical statistics, epidemiology, health economics or a related field. Relevant experience in applying
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PhD) while conducting highly policy relevant research. Applicants should have a postgraduate degree with MRCP or MRCS. Relevant clinical experience in providing cancer treatments, co-ordinating clinical