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Field
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therapy (Simpson et al. in preparation*). When these local metabolic / immunologic changes happen during pancreatic cancer evolution remains unknown. More importantly, whether these spatial changes can be
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validated surface functionalisation methods that significantly improve metascintillator performance, accelerating the development of advanced radiation detectors for ToF-PET and enhancing early cancer
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. However, there are significant challenges to a broad proof of concept that would be addressed in this PhD project. Laser beam sources, process development and control to enable better control of mass
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reduce unsustainable costs?’ The research will include: Evaluating the initiatives already in place and being developed Reviewing how other places have solved similar issues Feeding back the above findings
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development could be foreseen in Year 4. The recruited PhD candidate will become a member of an active research group working on the development and application of cutting-edge computational techniques
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for next-generation gas turbines. These geometries pose manufacturing challenges, particularly regarding heat transfer, microstructure evolution, and defect prevention. Building on recent doctoral research
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aerospace and the technologies used to decarbonise flight The following skills are desirable but not essential: Ability to code program in Matlab Experience using CFD codes. Experience with heat transfer
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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target, since all known treatment resistance mechanisms are downstream of, and dependent on FOXA1. However, FOXA1 has been a difficult protein to study for technical reasons. We have developed a novel tool
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Ascl1 are important. We have undertaken a comprehensive discovery experiment to identify all the proteins that can physically interact with Ascl1, using a method we developed called RIME (Rapid