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with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates, hands on skills in implementation of fusion/learning based techniques in
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
) in a relevant discipline such as aerospace engineering, mechanical engineering, electrical engineering, computer science, applied mathematics, or a closely related field. Experience or interest in
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on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form. Applications should include a Curriculum Vitae, contact information
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honours degree (2:1 with 65% average), or international equivalent, in Engineering, Computer Science, Physics or Mathematics with evidence of programming experience. Equality, diversity and inclusion is
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Rolls-Royce, this project will use both experimental and computational aspects to explore the aerodynamic design space for coupled intake/fan configurations that are required to deliver more efficient
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. Experiment with ultrasonic sensors for real-time seal gap measurement. Combine experimental research and mathematical modelling to pioneer innovative sealing solutions. What We Offer Full 4-year Funding for UK
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for the probability of occurrence of FBO responses. Applications are invited for a fully fundedPhD studentship (UK or EU or International) working on the project. The PhD student will join Rolls Royce Computational
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to study corrosion, cracking and mechanical degradation, develop advanced computational models using modern C++ and high-performance computing to simulate material behaviour over a 100+ year timespan. This
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Engineering Research Group) Aim: Develop a mathematical model for analysing reliability and efficiency of medical processes Background Adverse events and preventable failures in healthcare services represent a
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with engineering, physics, mathematics, acoustics, fluids, electronics or instrumentation background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience