107 parallel-computing-numerical-methods positions at University of London in United Kingdom
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points throughout the flexible programme. You will work within a team of Student Experience and Programme Delivery Managers and be supported by a team of Programme Administrators, in assisting
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motivated computational Postdoctoral Research Assistant to lead on an established and successful research line aimed at understanding the genetic events that drive cancer evolution. We have a long-lasting
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care and preventive medicine. The post-holder will work in the Centre for Evaluation and Methods (CEM), a thriving centre that incorporates collaborative units who work to deliver outstanding research
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procedures and internal policies. Applicants will have proven relevant experience of working in research, with excellent organisational skills, excellent written, oral communication and numeric skills
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-of-the-art computing facilities and collaborate with experienced Co-Is at Royal Holloway’s Computer Science Department and UCL’s Advanced Research Computing Centre as well as Project Partners
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triggers, and applying cutting-edge AI methods, the tool will provide detailed insights into patient state and asthma management. Data will be collected and analysed within QMUL, Huma, and Bart’s NHS
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demonstratable knowledge in advanced statistical methods (e.g., time series regression, binomial regression, Poisson regression, Cox regressions) and scientific academic writing. Further particulars are included
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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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in working with large-scale electronic health records (EHR) data, and ideally with strong analytical skills. The post-holder will be expected to apply various analytical methods using EHR data