26 big-data-and-machine-learning-phd Fellowship positions at University of London in Uk
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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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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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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
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for this and other related grants held by the group, including coordinating meetings with coinvestigators and stakeholders, contributing to writing of publications and contributing to quantitative data analysis
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Infectious Disease Epidemiology & Dynamics department at LSHTM to work on polio eradication. This role utilises global surveillance data for polio to inform understanding of the status of eradication and
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Drakeley and Dr Julius Hafalla, primarily focused on immunoepidemiology, as needed. The post holder will be responsible for the generation and curation of laboratory and epidemiological data from different
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paragraphs addressing each criterion. The supporting statement is an essential part of the selection process and thus a failure to provide this information will mean that the application will not be considered
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experience in lab-based microbiology, virology and cell culture techniques. Further information is available in the job description/person specification. The post is full-time 1 FTE and fixed-term until 31st
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-led nutrition interventions during the war in Sudan. Responsibilities include developing surveys to assess reliance on community kitchens, analysing pre- and post-war data on food, disease, and coping