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(conductivity, heat capacity, flame resistance). Advanced finite element modelling will then correlate microstructural features to heat-transfer performance. The candidate will design and build a burner-rig test
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are essential to meet the demands of next-generation applications. This PhD project offers an exciting opportunity to pioneer separator-free battery architectures using ultrathin, high-performance coatings made
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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state-of-the-art high heat flux testing, simulating the extreme environments of fusion reactors. Harness advanced computational tools to model complex particle-material interactions and predict material
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, with minimal computational cost. By developing an advanced reduced order modelling framework, this project will empower engineers and designers to achieve more with less—delivering high-impact decisions
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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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October 2026 start ONLY For January and April starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme at
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these, and then determine their imaging performance in bespoke optical systems in the visible light range. Applicants should have, or be expected to gain, a high (1st or 2:1) honours degree in Physics or Electrical
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these, and then determine their imaging performance in bespoke optical systems in the visible light range. Applicants should have, or be expected to gain, a high (1st or 2:1) honours degree in Physics or Electrical
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computational methods to optimise the quality of doubly curved shell structures manufactured from recycled, short-fibre composites. A particular novelty of the research will be the inclusion stochastic elements