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demonstrated experimental realizations and proven theoretical advantages. The project may involve several aspects, including mathematical theory, algorithm development, error correction, adaptation of GBS-based
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, introduces human error, and creates line-of-sight occlusions, disrupting surgical workflow. This interdisciplinary project aims to overcome these challenges by developing a vision-based marker-less navigation
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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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through accidental faults and targeted cyberattacks and how large scale constellations can achieve the same properties to protect for example, our energy grid. This position is initially funded for three
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-error approach due to a lack of comprehensive hormone testing data. This project aims to demonstrate that frequent hormone monitoring, combined with education and symptom monitoring, will improve
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projects within the Centre for Assured and Connected Autonomy. The research will significantly enhance aircraft maintenance processes by reducing inspection times, costs, and human error risks. It will
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
generate vast amounts of operational and maintenance data, much of it remains fragmented and underutilized. Unlocking insights from this unstructured data could enable earlier fault detection, improved
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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parameters by trial-and-error, leading to a time consuming sub-optimal selection. In the domain of high precision machining, tools are prematurely discarded to avoid the risk of costly non-conformities
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magnification and error accumulation by closing the feedback loop of conventional 3DP systems. The candidate will test the developed technologies across multiple application scenarios, including large-scale