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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
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performance degradations and unwarranted system failures can occur. There is certain physical information known a priori in such aerospace platform operations. The main research hypothesis to be tested in
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, the technology developed here could be easily adapted for aerospace conditions. You will work in a multidisciplinary environment consisting of material scientist, chemists, engineers, physicists
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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systems safer, more efficient, and more sustainable. The aim of this project is to design a smart cognitive navigation framework that information from various sensors and learn to make decisions on its own
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existing data analytics tools will help deploy these technologies in the industry context without the need for big datasets. Predictive Maintenance (PdM) is one of the maintenance strategies that has
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
amounts of maintenance and operational data, from sensor streams to technical logs, yet much of it remains unstructured, fragmented, and underused. Hidden within these records are insights that could help
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, finance, and healthcare, where data integrity and system reliability are non-negotiable. This PhD project addresses the integration of robust security measures within AI-enabled electronic systems
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subsurface and internal temperature distributions. Semi-destructive approaches, such as embedding thermocouples by drilling holes, can provide internal data but often disrupt the process, alter the thermal