62 computer-science-intern "https:" "https:" "https:" "https:" research jobs at University of London
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and the Francis Crick Institute. This initiative brings together world-class experts in evolutionary genomics, stem cell biology, and computational science to unravel one of the most fascinating puzzles
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, and functional genomics. The Biology Department hosts its own genomic facility and has recently developed a Research Centre on the theme: The Centre for Evolutionary and Functional Genomics (https
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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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within a multidisciplinary research team. About the School/Department/Institute/Project The School of Engineering and Materials Science is a large, multidisciplinary School with a strong international
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biomarkers. About You Candidates must be educated to degree level or equivalent in a relevant medical science discipline. The ideal candidate will have a background in clinical research and be familiar with
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School, we are known for our pioneering research and pride ourselves on our international reputation. We are equal first in the UK for the impact of our Computer Science research, and second for our
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systems shape the experiences of migrants and the practices of welfare bureaucracies. The successful applicant will be based in the Department of Sociology, Politics and International Relations at Queen
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with a PhD in physics, mathematics, computer science, mathematical/computational biology, evolutionary theory or cancer genetics. About the Institute The Barts Cancer Institute (BCI) is a Cancer Research
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to a broader computational strategy for next‑generation polymer design. About You You will have, or be close to completing, a PhD in materials science, engineering, physics, chemistry, or a related area
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(e.g. molecular biology, bioinformatics, artificial intelligence or statistics), with strong computational skills and experience working with genomic or large-scale biological datasets. Further