17 parallel-computing-numerical-methods-"Prof" Fellowship positions at University of London
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empirical research. They will oversee specific research tasks, develop new techniques, and generate original contributions to the programme while fostering a collaborative team environment. Key
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Applications are invited for this PhD training programme to commence in September 2026. Led by the London School of Hygiene & Tropical Medicine, this PhD Programme is offered by five UK and six
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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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, the models will incorporate novel estimates of vaccine waning and account for variation vaccine effectiveness across different populations within the UK. The post will be part of a large research programme on
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the College’s small animal referral hospital by further developing and delivering advanced cardiac surgical therapies through the open heart surgery programme, at the Royal Veterinary College. We are looking
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the study in collaboration with research teams at Nottingham, Oxford, UKHSA and Manchester with expertise in mixed-method policy evaluation, antimicrobial resistance, pharmacy practice research, primary care
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in methods of evidence synthesis with a focus on complex public health topics is essential. They should contribute to written outputs, preferably peer-reviewed, consistent with disciplinary
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software packages. They also must have demonstrated knowledge of longitudinal data analysis methods, and an understanding of sample size calculations. Further particulars are included in the job description
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epidemiological or econometric methods, using R software package, and an understanding of techniques used in agent-based modelling. The post is full-time 35 hours per week, 1.0 FTE and fixed term until 31 December
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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