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                AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhDmechanics, and artificial intelligence (AI)—specifically in the domains of non-destructive evaluation (NDE), computer vision, and machine learning. It addresses a critical challenge in the structural health 
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                Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel 
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                control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands 
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                critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo 
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                results from the Advanced Propulsion Centre (APC)-funded CERABEV project. The candidate will develop expertise in: Understanding of battery thermal runaway mechanisms and standards. Design and deposition 
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                paramount. Secure and trustworthy AI-electronics focus on embedding security features directly into hardware, such as hardware security primitives and tamper detection mechanisms. This field addresses 
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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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                second class UK honours degree or equivalent. This project would suit an applicant with a materials science/engineering, mechanical/chemical engineering or chemistry background or a related discipline 
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                play a very vital role in the operation and availability of rotating machinery. Despite successful implementations in industrial applications, CM of bearings still poses many challenges. One 
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                . The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned