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of light. [1][2] This emerging technology holds enormous potential, offering routes towards new forms of highly parallelised information processing (optical computing), point-of-care diagnostics, next
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experiment. In addition, the manipulation of multiple resonances at ultra-low temperatures is a promising technique for coupling signals in and out of other electromagnetic structures, including arrays
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should be both chemically and mechanically stable under typical industrial conditions moving from post-combustion process to direct air capture (DAC) technology. However, there will be a particular focus
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-driven AI models that capture the underlying process–structure–property relationships governing metal additive manufacturing. By combining mechanistic modelling, in-situ sensing, and machine learning
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understanding of polymer behaviour. You will use and develop molecular simulation tools to study curing reactions, network formation, and structure–property relationships in industrially relevant epoxy‑amine
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and scale. They will work across research communities, funders, infrastructure providers, technology partners and senior stakeholders across UKRI and government to embed community voice into the design
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Physics-Informed Digital Twin for Guided Wave-Based Structural Health Monitoring (SHM) of Offshore Wind Turbine Foundations
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focus is estates, construction, maintenance, and facilities management, the role may also support wider University procurement initiatives as required. Key responsibilities will include: Developing and
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Bridging Causality and Forecasting in Space Weather: A Transparent Complex Systems Modelling and Interpretable Machine Learning Framework School of Electrical and Electronic Engineering PhD Research
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Space - Potential Mapping Using 4D STEM project. Role Overview Our team of physicists, engineers, biologists and mathematicians focuses on electron microscopy theory, method and technology development