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University provides an ideal setting for this research, offering a wealth of resources and expertise in engineering and digital technologies. The expected outcome of the project is the development of novel
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This PhD project will focus on developing, evaluating, and demonstrating an intelligent solution of diagnosis and prognosis for rotating machinery to enhance safety, reliability, maintainability and
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in a related discipline. This project would suit motivated graduates from a wide range of STEM backgrounds—including environmental, civil, chemical or mechanical engineering, computer science, robotics
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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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lifespan under fusion conditions. Apply innovative materials characterisation methods to reveal fundamental structural and mechanical transformations. Uncover and quantify critical degradation mechanisms
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technologies. Metamaterials, engineered to exhibit properties not found in naturally occurring materials, offer an innovative pathway to overcome these limitations. By designing intricate periodic or quasi
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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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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
) in a relevant discipline such as aerospace engineering, mechanical engineering, electrical engineering, computer science, applied mathematics, or a closely related field. Experience or interest in
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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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