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opportunities for better design. AI-driven optimisation offers a promising parallel route forward. Techniques such as Bayesian optimisation have already proven successful in related contexts, such as optimising
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application, developed through parallel funding. The project sits at the intersection of Life and Health Sciences and Software/Cyber innovation, aligning with Northern Ireland’s strategic goals for Med-Tech
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competitive manufacturing pathways. The Project: Metal additive manufacturing (or 3D printing) has been rapidly adopted by industry. The metal additive process is unique as it allows for the manufacture
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integrating local waste streams, renewable energy, and CO₂ reuse, the project aims to reduce the production costs of renewable methanol. Biowaste electrolysis is an emerging process (TRL 3) for green hydrogen
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managing the improvement process. This research will focus on the UK NHS. It is anticipated that a mixed methodology will be employed incorporating action research with qualitative research. Essential
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, biodiversity monitoring, and climate resilience. The work supports strategic priorities in Environmental Sciences, Software/Cyber. PhD researchers will explore how AI-driven Earth observation, computer vision
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-spinning, embedding heritage within process and sustaining Donegal’s unique position in international markets. The research addresses contemporary challenges facing the wool industry synthetic competition
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significant complication rate of around 7 – 10 % including pain, joint swelling, stiffness and hemarthrosis post-operation [1,2]. With over 103,000 primary knee replacements in the UK in 2022 alone [3
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approaches leads to the generation of a powerful, immune-mediated effect that could potentially be exploited to treat metastatic cancer [3]. Whilst use of the above listed approaches provides enhanced
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through the vessels and how diseases like heart blockages or artery wall damage develop. However, most current computer models used to study blood flow treat arteries as if they are rigid and motionless