19 software-formal-method-phd Fellowship positions at University of London in United Kingdom
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data from the UK using robust causal inference methods. Based in London at the London School of Hygiene & Tropical Medicine, the post-holder will be embedded within the Electronic Health Records Research
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science methods, ideally to environmental health data, and conducting systematic reviews and meta-analysis. Further particulars are included in the job description. The post is full-time 35 hours per week
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demonstrable experience in analysing datasets such as infectious disease surveillance, applying statistical methods, and interpreting output. Further particulars are included in the job description. The post is
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mitigation priorities for the UK. Candidates should also be experienced in conducting quantitative research and applying spatio-temporal epidemiologic methods, ideally to environmental health data. Further
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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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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 behaviour change science as applied to obesity-related NCD research and experience in undertaking behavioural analyses and mixed-methods evaluations of obesity-related NCD interventions. Further particulars
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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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addressed to jobs@lshtm.ac.uk . A short (500 words) planetary health related research proposal including appropriate methods and outcomes and feasible in a 2-year timeline, are to be submitted alongside your