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challenge of our time, and it is more urgent than ever to act fast on reducing greenhouse gas emissions from current chemical manufacturing processes. Plasma technology provides a sustainable, fossil fuel
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composites To propagate uncertainty in material behaviour through these models using uncertainty quantification/machine-learning (UQ/ML) algorithms To optimise the manufacturing process with the help
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, they can utilise temporal and spatial diversity whilst simultaneously exploiting shared, intelligent adaptive signal processing whose combined performance and resilience can easily exceed that of the sum
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computer vision method for medical image analysis principally in oncology or pathology, with a possible focus on generative AI, explainability, multi-modality. Candidate’s profile A good Bachelors degree
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processes, exploring wave energy propagation and other marine hydrodynamics towards minimising uncertainty of low resolution datasets Participate in research aimed at the dynamical downscaling of ocean models
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Conventional metal mining, in which minerals are physically extracted from the subsurface and then processed to recover target metals (which often make up only a small fraction of the total mass) is
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PhD studentship in Bio-electronics – Localising invisible breast cancers during surgery Award Summary 100% fees covered, and a minimum tax-free annual living allowance of £20,780 (2025/26 UKRI rate
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diagnoses annually. Surgery (lumpectomy or mastectomy) is the best line of treatment. To enable surgeons to identify the cancer tissue, radiologists insert a localisation device (RFID, magnetic seed
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data, and digital process tools to support the scalable production of resilient, build-ready reactor components. Please contact Dr Kai Zhang (k.zhang@bristol.ac.uk) for further information. This project
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The School of Computer Science at the University of Nottingham is pleased to invite applications for a fully funded PhD studentship in deployable, efficient, and trustworthy computer vision. This is