37 professor-computer-"https:"-"https:"-"https:"-"https:" research jobs at University of London
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About the Role We are looking for a Computational Senior Research Fellow to join the ERC-Synergy funded MUTAHOME project, a multi-institutional collaboration between Queen Mary University of London
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Computer Science at Queen Mary University of London, working with Professor Rachel Humphris and Dr Dimitrios Kollias. The successful applicant will undertake computational research, including algorithmic
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. Supported by a BHF Programme Award, this role offers an excellent opportunity for a motivated clinician to pursue academic cardiology in a leading research environment. The Fellow will contribute
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. The salary will be Grade 4/25 – 4/26 at £38,419 - £39,022 per annum, inclusive of London Allowance. Informal enquiries should be addressed to Professor Alastair Noyce at Dr Eduardo de Pablo-Fernández
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behaviour observed in laboratory studies. You will work closely with Professor Kostas Stathis (Department of Computer Science, Co-Investigator) and Professor David Levine (Leverhulme Fellow and Principal
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with Professor Emma Thomson and Professor Michael Marks, and collaborators at UKHSA. This work is a collaboration between the London School of Hygiene & Tropical Medicine (LSHTM), the Rare and Imported
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Mary University of London and will work under the supervision of Professor Rachel Humphris. They will lead in-depth ethnographic fieldwork in Sweden, undertaking interviews and participant observation
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surgical procedures. The project is led by Professor Kaspar Althoefer within the Centre for Advanced Robotics @ Queen Mary (ARQ), a hub for robotics innovation and interdisciplinary collaboration. About
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will develop and apply computational methods for the analysis of cell-free DNA (cfDNA) sequencing data, supporting a growing research program at the intersection of epigenomics and translational medicine
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under the supervision of Professor Rachel Humphris. They will lead in-depth ethnographic fieldwork in the Netherlands, undertaking interviews and participant observation to trace how welfare algorithms