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to support smart manufacturing, operation and monitoring of industrial processes and equipment. Digital twins (DT) are multiphysics, multiscale, high-fidelity simulation that emulate in real-time the state
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withstand the high loads and start-stop nature of operation. This project is about supporting those developments. Some questions that will need to be addressed: will conventional bearing facing materials
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that operate with minimal computing, sensing, and actuating resources—essential features for implementation in real-world scenarios. To this end, we will leverage sophisticated mathematical tools such as
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-breathing lung MRI. Image computing support for pulmonary MRI applications. Support the development of a prototype neonatal pod for lung MRI, in collaboration with industrial partner, Contribute
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of working as part of a collaborative team and a willingness to supervise PhD and undergraduate students (assessed at: application/interview) Ability to motivate high performance in others (assessed
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machining performance. The Challenge Tool coatings are designed to withstand extreme heat in conventional machining, but SCCO₂-assisted machining significantly lowers cutting temperatures. This raises
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facing the UK’s programme of remediation and restoration of the Sellafield site, expected to be complete in the next century. The PUMaS hub will support ~20 PhD students along with research staff, creating
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skyscrapers, or improving the energy efficiency of mechanical systems, advanced control methods are at the heart of these challenges. Effective control mitigates vibrations, boosts performance, enhances energy
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technology that not only enhances signal coverage but also revolutionizes the way we control antennas, reducing system complexity, and paving the way for high-speed, efficient mobile communications. Project
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) tool to overcome this critical bottleneck in the development of MHPs. Working with a multidisciplinary team, the student will combine predictive machine learning techniques and high-throughput