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project is to develop a series of surrogate models focusing notably on Physics-Informed Neural Networks to emulate the process of sediment deposition, diagenesis, and potentially fracturing, working closely
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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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Grant “Advancing Gravitational-Wave Astronomy Using Artificial Intelligence” led by Dr Greg Ashton. The successful candidate will join Royal Holloway’s Astronomy Group and conduct research activities
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that demonstrates this effect on a laboratory scale, and that can be used to test the operando performance of various barocaloric materials and heat exchange structures. We are looking for a researcher to develop
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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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complex study. Applicants must have a PhD in a relevant subject. The study requires substantial skills in cell and molecular biology and will require vivo testing of the newly created cell-models. Omics
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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
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and spatial transcriptomics is desirable. You should have experience working in interdisciplinary teams, bringing together computational, experimental, and clinical expertise to advance ground-breaking
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Group and conduct research activities related to the modelling of the interiors of compact stars. This post will specifically focus on the cross-disciplinary area of cosmic superfluidity in ultra-dense
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the nature of celestial objects, the evolution of galaxies, and the structure of the Universe itself. We are also actively involved in the utilisation of upcoming facilities such as the Square Kilometre