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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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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
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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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applications using an existing agent platform Evidence of a publication record in good quality journals Experience/expertise with computational modelling of agent models and behaviour. Practical experience
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of random mathematical structures including many applications to areas such as statistical physics, finance, etc. The centre also has a strong group of statisticians developing both statistical theory, e.g
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-person workshops, convene thematic Working Groups (WG) to advance methodological approaches, and strengthen local networks with the overarching intention of facilitating challenging discussions, sharing
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experimental approaches to develop and validate novel in vitro and ex vivo approaches that model arterial medial calcification without using any animal products. This work will represent an exciting step forward