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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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research project on cardiovascular risk prediction for people with immune-mediated inflammatory disease. The successful candidate will use advanced risk prediction methods to develop prediction models
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is Prof Cally Tann. We are seeking a Research Fellow in Early Child Development & Disability to coordinate the development, implementation and evaluation of the programme, including: mixed methods
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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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), and apply these and other related methods in a study comparing the clinical and cost-effectiveness of local versus general anaesthetic for people with a ruptured abdominal aortic aneurysm undergoing
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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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, involved in study set up, trial management, and data analysis. The data analysis component will be primarily of genomic data. The purpose of this post is to identify and investigate genotype-phenotype
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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