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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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the successful applicant will be very well positioned to have a highly successful career in the water sector or in an academic role. We will help you develop into a dynamic, confident and highly competent
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attracted intense interest from both academia and industry recently for its attempt to extract more useful information and knowledge from Big Data. Big Data analytics will help to develop more advance
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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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propulsion systems. You’ll join the wider CDT multidisciplinary cohort that values equity, diversity, and inclusion, while gaining expertise in aero-engine aerodynamics, analysis of advanced experimental data
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application form. For further information please contact: Professor Weisi Guo weisi.guo@cranfield.ac.uk
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. The developed new knowledge will assist performance designs, analysis, operations, and condition monitoring of sCO2 power generation systems. The project will be undertaken using the strong thermodynamic
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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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with a wealth of social and networking opportunities. How to apply For further information please contact: Name: Professor David MacManus Email: d.g.macmanus@cranfield.ac.uk If you are eligible to apply