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postgraduate degree, ideally a PhD, in statistics, machine learning, or a related field. Experience of developing new statistical methods and a strong working knowledge of a statistical software package, such as
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independently and in close collaboration with in-country partners. The applicant should have an excellent academic track record that includes formal training in microbiology as well as a relevant PhD (public
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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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of the research project and develop new areas of research. The post-holder will be expected to undertake a higher degree such as a PhD during the fellowship. About You The applicant must be a medically qualified
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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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will have a PhD in a related field, an emerging track record of outstanding publications, and well-developed plans for new research projects. This post is generously funded by the A. G. Leventis
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Research Fellow. The successful candidate will be a medical doctor with experience of providing cancer treatments (radiotherapy or surgery), and will join a new NIHR-funded research project called TACTIC
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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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analytic codes to investigate the benefits and harms of medications. Candidates must have a doctoral degree (or be within 3 months of anticipated completion of a PhD) in medical statistics or epidemiology
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at LSHTM. Applications should be made on-line via our jobs website . Online applications will be accepted by the automated system until 10pm of the closing date. Any queries regarding the application process