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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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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
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environmental epidemiology research team at LSHTM to work on a new UKRI-funded study in the field of climate change and health entitled THERM-UK. This is an exciting opportunity to be part of a large
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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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have a postgraduate degree, ideally a doctoral degree, in a relevant field and experience in computer-based analyses and presentation of experimental data. The successful applicant would have a proven
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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
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doctoral degree, in sexual and reproductive health or a relevant subject/discipline and a recognised teaching qualification equivalent to the LSHTM Postgraduate Certificate in Learning and Teaching, or to be