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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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, in collaboration with Rolls-Royce, will develop innovative coatings to safely contain hydrogen in critical aerospace materials through experimental and computational modelling work. You’ll join a
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in a related discipline. This project would suit motivated graduates from a wide range of STEM backgrounds—including environmental, civil, chemical or mechanical engineering, computer science, robotics
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with: • Experience with programming (Python, MATLAB), • background in aerospace, computer science, robotics, or electrical engineering graduates, • hands on skills in
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honours degree in materials science, physics, engineering, or a related discipline. The ideal candidate will be self-motivated, with an interest in both computational modelling and practical manufacturing
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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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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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in radiation–matter interactions, computational modelling, and materials science, with a strong publication record (h-index 36, i10-index 69). Dr Francesco Fanicchia, Research Area Lead: Material
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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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-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