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Field
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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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objective is to find the best way to embed simple partial differential equations into AI-based models to solve fluid sensing problems in a robust and efficient manner. Your role may include developing new
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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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healing, haemostasis promotion and water treatments). The objectives of this project focus on evaluating the antibiofilm efficiencies of different Chitosan derivatives with various polymer sizes and to
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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, commissioning cost, lifetime maintenance, replacement and disposal costs and environmental costs also add up to the total evaluated cost of a transformer. Different objective functions in terms of minimisation
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of seaways by a broader spectrum of people than previously appreciated. Welsh connections have been studied in detail for the early medieval period but new excavated and stray-find evidence from the later
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with inflation). Research training and support grant (RTSG) of £3,000 per year. Funding is available for 4 years. Closes: Open until position filled The overarching aim of this project is to find
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to research together with a strong intellect and disciplined working habits. Good team-working, observational and communication skills are essential. Training will be provided according to the objectives
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Bayesian inference framework for identifying complex aerospace systems combining with limited experimental data. It can be also used to quantify uncertainties from experimental testing, significantly