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quality, diversity, and biological relevance using standard metrics and expert review. Anonymised digital images from tissues in biobanks will be used to train generative models on university computing
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programme; please do not use any other link to apply to this project or your application may be rejected: https://sits.bham.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=FR167D&code2=0005
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through the EU Research Framework Programme? Not funded by a EU programme Reference Number RS904 Is the Job related to staff position within a Research Infrastructure? No Offer Description ALL-WALES
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bioprinting, materials characterisation, and computational modelling to replicate and quantify biomechanical conditions. Number Of Awards One Start Date January or April 2026 Award Duration 4 Years Application
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and programmable biomaterial synthesis. The ability to program the behaviour of biomolecular chemistry is foundational for developing new biotechnology applications. Redox-sensitive molecules are a
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of high-resolution multibeam bathymetry and flow surveys, enabling detailed analysis of how riverbeds evolve under and after mining. These observations will be complemented by physical experiments in
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Turkmendag Eligibility Criteria We are adopting a contextual admissions process. This means we will consider other key competencies and experience alongside your academic qualifications. An example can be
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, Newcastle University Eligibility Criteria We are adopting a contextual admissions process. This means we will consider other key competencies and experience alongside your academic qualifications. An example
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
intelligence, particularly in computer vision and deep learning, offer an opportunity to automate and enhance damage assessment by learning patterns from multimodal data. This research seeks to bridge the gap
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our ability to predictably control and exploit the drop for useful tasks. The proposed project has two aims: First, to develop computational models to quantitatively predict the response of chemically