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profoundly affect their mechanical properties and overall performance. Therefore, understanding the temperature field and developing effective thermal control techniques are vital to ensuring a high-quality WA
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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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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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, operation, and monitoring to reduce land requirements, optimise nutrient removal, and deliver broader ecosystem benefits. The research will combine field monitoring at a newly constructed wetland with
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for Rotating Machinery Faults: A versatile platform that replicates common faults in rotating machinery, such as imbalance and misalignment, facilitating the development and validation of diagnostic and
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, isolation, and prognostics. Machine Fault Simulator for Rotating Machinery Faults: A versatile platform that replicates common faults in rotating machinery, such as imbalance and misalignment, facilitating
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Power is one of the largest research and education activities within the University. The activity spans across land, off-shore, marine, air and space power and propulsion applications, with a particular
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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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microstructure, residual stress, and distortion of the deposited parts, all of which significantly impact their mechanical properties and overall performance. Consequently, accurately determining and effectively
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through elucidating the mechanisms that enhance soil function and soil health in plantations, and by advancing molecular breeding approaches in a long-standing tea breeding programme. The role will be