577 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "The University of Hong Kong" uni jobs at University of Sheffield
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undertaken by the EPSRC Doctoral Landscape Award at the University of Sheffield. Structural Health Monitoring (SHM) is the process of using real-time sensor data from high-value engineering assets to inform
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duties and responsibilities Make an active contribution to the establishment of novel instrumented external test beds, and in developing suitable tools for the data analysis activities planned in
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property. Capturing the photons enables the spin-based sensor to function as an extremely sensitive monitor of its immediate environment, as information can now exit the environment, free from
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can damage cables and pipelines that carry electricity and data across the ocean floor. Such events can disrupt power transmission and communications, creating major operational and financial challenges
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and clinicians without reliable data to inform treatments. This PhD project directly addresses these challenges by developing an innovative wearable device that comfortably and discreetly captures vital
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environment. Desirable Application Further Information Grade Grade 4 Salary £25,249 - £26,707 per annum (pro rata) Work arrangement Part-time (80%) Duration 1 April 2026 - 24 December 2026 Line manager
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energy infrastructure is designed with a focus on efficiency and reliability under “normal” conditions. Traditional risk assessment methods look at historical data and isolated failure scenarios. But in a
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electronic devices. Yet, despite this potential, no examples of information-rich 2D materials have ever been created. Nature, provides a blueprint. Biological macromolecules such as DNA and proteins store and
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at the University of Sheffield. Single photons are the indispensable information carriers for core quantum technologies, including quantum communication and computation. The critical hurdle is the reliable
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using deep learning. These data-driven approaches have proven to be highly flexible and powerful, able to generate nonlinear control policies able to act on the nonlinear plasma dynamics by learning