44 algorithm-development-"University-of-Surrey" research jobs at University of London
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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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to work with an international team on developing cutting-edge novel demographic, statistical and computational methods in estimating, modelling and forecasting measures of health, well-being, and human
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project developing Bayesian causal inference methods for mediation analysis using Electronic Health Records (EHR) data. The Research Fellow will design and implement Bayesian methods and software
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applicant will work in Professor Rastle’s lab. The post is based in Egham, Surrey where the University is situated in a beautiful, leafy campus near to Windsor Great Park and within commuting distance from
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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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analysis to join a dynamic team that has, for the past 8 years, developed an extensive body of research on corruption, governance and anti-corruption strategies. In the Accountability in Action project
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ticket loan scheme and access to a comprehensive range of personal and professional development opportunities. In addition, we offer a range of work life balance and family friendly, inclusive employment
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: 23.59 hours BST on Tuesday 26 August 2025 Interview Date: Wednesday 03 September 2025 Reference: PPS-0210-25 We are seeking a highly motivated Post-Doctoral Research Assistant aiding the development
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closely with Dr Ija Trapeznikova , Dr Ahu Gemici and Prof Juan Pablo Rud . As part of the research team, the RA will work on cleaning, standardising and organising secondary data for a number of developing
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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