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Technology Laboratory (DSTL), Electromagnetic Environment (EME) Hub. About You Applicants should have a PhD in modelling hypothetical scenarios, with and without data, for structured decision-making under
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Computer Science or a related topic. Applicants at the PDRA level must have a PhD in NLP or machine learning. Substantial knowledge of Natural Language Processing (NLP) and machine learning methods is essential, as
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mortality using traditional and new forms of data, with a focus on developing and low-income countries. The successful applicant will spend 18 months at LSHTM and enrol in the PhD programme, with fees funded
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researchers and industrial collaborators on the research project. About You The candidate should have a PhD (or close to completion) in a biological, biomedical or closely related science. Previous work
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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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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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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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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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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