31 high-performance-computing-postdoc Postdoctoral research jobs at University of London in United Kingdom
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. The post-holder will participate in lab meetings, journal clubs, departmental research meetings, and co-supervise students. They will also present data at high-profile international and national meetings
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, the successful candidate will have an independent 3-year research agenda delivering high quality research. The successful candidate will play a role in establishing an interdisciplinary network on war and violence
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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About the Role We are seeking a researcher for a new programme focused on improving understanding of cancer risk and developing novel multicancer risk prediction models to support cancer prevention
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About the Role The purpose of this role is to provide qualitative and quantitative research support for a research and impact programme on food reformulation. This role sits within the Research and
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environment in a well-established research team working on a variety of high-priority Thoroughbred welfare projects. We offer a generous reward package including: • Competitive and attractive pension
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About the Role This role will involve undertaking the evaluation of a digital social intervention in primary care in England. A summary of the programme grant is found here. The individual will be
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responsibility for implementing a deep learning work-package as part of a Cancer Research UK-funded programme, developing an image-recognition model to identify morphological features corresponding to clonal
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related to gravitational wave astronomy. The primary aim will be the development of advanced approaches for computational Bayesian Inference to measure the properties of Compact Binary Coalescence signals
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing