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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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project investigating mechanosensing in Diptera. This post will focus on using detailed wing geometry models and kinematic measurements in computational fluid and structural dynamics simulations to recover
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and
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Institute (BCI) in London, with an ideal start date of July 2025. About You The successful candidate will be highly-motivated, have a PhD (or close to completion)* in a biological or computational discipline
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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network including epigenetics experts (QMUL Centre for Epigenetics), cardiovascular geneticists (Prof. Patricia Munroe) and computational collaborators (Dr. Camille Berthelot). About You We seek
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to refereed journals, and work with and help supervise BSc, MSci, and PhD students. The successful applicant will have a PhD in Astrophysics, Theoretical Physics, or a related discipline and prior experience
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to someone proactive and ambitious who has obtained their PhD and has begun an academic career in epidemiology, pharmacoepidemiology, or medical statistics, with a focus on causal inference methods applied
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Research Council’s (AHRC) Bridging Responsibilities AI Divides (BRAID) programme that will explore new technologies, new business models and new approaches to data provenance in pursuit of an equitable