10 Computer-Science-"https:"-"https:"-"https:"-"https:"-"https:"-"Imagine-Institute" Fellowship positions at University of London
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Science, Statistics or Epidemiology x2 (0.5 - 1.0 FTE) Department Health Services Research & Policy Salary £45,728 to £51,872 per annum pro rata inclusive Closing Date Thursday 27 August 2026 Reference
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Asked Questions Cookies Contact Us Teaching Fellow, Senior Teaching Fellow, or Lecturer in Animal Behaviour and Welfare Science We invite applications for a 3-year part-time Teaching Fellowship, Senior
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inference workflows. The project engages UK-government stakeholders, reflecting its policy relevance. Applicants should hold a postgraduate degree, ideally a doctoral degree in computer science
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mental health outcomes led by Dr Neisha Sundaram and funded by the National Institute of Health Research within a randomised controlled trial of the ‘Learning Together for Mental Health’ intervention
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formal training in economic evaluation and related methods. The post is full-time 35 hours per week, 1.0 FTE and fixed term until 31 March 2028. The post is funded by the National Institute for Health
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. The post is funded by the National Institute for Health and Care Research (NIHR) and is available from 01 October 2026. The salary will be on the LSHTM salary scale, for Research Fellow Grade 6 in the
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and Training Institute, Zimbabwe (BRTI), MRC The Gambia (MRCG), and MRC/UVRI & LSHTM Uganda Research Unit (MRCU). Together these institutions have exceptional resources and an outstanding track
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experience in computer-based statistical analysis and presentation of results, demonstrated proficiency in a coding language used for data analysis, such as Python or R, proof of previous data analysis
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based in Uganda. The successful candidate will have a postgraduate degree, ideally a doctoral degree, in the field of public health, psychology, science or other related discipline. Proven experience in
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degree, in Climate Science, Environmental Health, Epidemiology, Statistics, Geography, Environmental Sciences, or a related discipline. A strong quantitative background, relevant experience in climate