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machine learning, this project will develop and validate a multi-time scale digital twin concept for advanced condition monitoring and maintenance of direct-drive permanent magnet generators and converters
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on machine elements, tribology, lubrication, and sensor systems for wind, auto, rail and energy applications. The group has well equipped labs and its own office space for the PhD students. https
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science, computer vision, medical/image analysis is essential. Experience of research (or interest in) in one or more of the following: deep learning; big data management; computational pathology; medical imaging
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: 30 June 2025 Details Join a project that will combine physics, machine learning, and ultrasonics to design new sensors for the digital revolution in industry. Ultra-thin membranes are produced in many
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explore data-driven methods including machine learning (ML) and artificial intelligence (AI) techniques, to develop predictive HMPM tools that can diagnose, detect, and predict faults in machinery
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significant advancements with the integration of Artificial Intelligence (AI) and Machine Learning (ML) techniques. This PhD research aims to explore the development and application of Process Induced Neural
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Physics informed learning for high fidelity medical simulators School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Sanja Dogramadzi Application Deadline
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subsystems • High performance tunable and reconfigurable oscillators and frequency synthesisers • Application of AI / Machine Learning to physical layer circuitry, signals and waveforms Researchers can expect
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Modelling, DEM simulations and Machine Learning Approaches. You will have access to the excellent training opportunities at the University of Sheffield. A range of highly desirable skills will be learnt
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capable of predicting boiling and CHF in PWR-relevant conditions. Combining improved physical modelling with the potential of machine learning and data assimilation techniques, you will specifically target