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innovation and find diverse applications across industries such as aerospace, energy, and automotive. Among its various techniques, wire-arc directed energy deposition (WA-DED) stands out as a highly promising
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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of the challenges is fault detection and diagnosis of bearings subject to low (rotational) speed. As vibration/acoustic signals generated by the faults of low-speed bearings are very weak and often covered by strong
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automated security systems that can detect and respond to dangers in real-time. With this opportunity, you will explore into cutting-edge technologies such as artificial intelligence, machine learning, and
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involves feeding a metal filler wire, either coaxially or off-axis, into an electric arc to create a molten pool that solidifies on a substrate, enabling the layer-by-layer construction of 3D objects
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research into fault detection, isolation, and prognostics. Machine Fault Simulator for Rotating Machinery Faults: A versatile platform that replicates common faults in rotating machinery, such as imbalance
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fitting for reduced order electrochemical models. Early detection of thermal anomalies in battery packs. Physics-based models and state of health estimation in lithium-sulfur batteries. Collecting data and
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through advanced modelling and simulation. A key objective is to validate and optimize poroelastic finite element models of brain tissue, making them more accurate and clinically relevant. Additionally
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studentship will work with conservation charities and citizen scientists to develop and validate innovative origami-paper eDNA sensors for the rapid detection of chemical and microbial contaminants in river
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. The enhanced image quality will support earlier and more reliable detection of eye diseases. Combining artificial intelligence with mathematical modelling, this non-invasive, cost-effective approach has