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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had
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in our CDT program, and warmly encourage applications from students of all backgrounds, including those from underrepresented groups. We particularly welcome students with disabilities, neurodiverse
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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October 2025. Later start date is possible, please contact Dr Isabella Guido once the deadline passes. You will need to meet the minimum entry requirements for our PhD programme. We are seeking a highly
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boundaries. This fully funded PhD scholarship is suitable for students with a background in Engineering Design, Smart Manufacturing, Aerospace Engineering, Mechanics, Computer Science, Mathematics, Life Cycle
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the PhD in Engineering programme. Make sure to reference the supervisor's name (Dr Farzad Hayati) in your application. Informal enquiries are welcome and should be directed to Dr Farzad Hayati at f.hayati
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training in computational tools and statistical methods over the course of the project. The project includes placements at NPL and Waters-TA Instruments, with opportunities to work in state-of-the-art
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for constraining the spin of the compact object being lensed which will involve both theoretical and computational modelling. If you wish to discuss any details of the project informally, please contact: Prof
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, requiring large computational effort to assess and study system stability. This is becoming even more challenging under increasing complexity requiring detailed dynamical models and with new dynamic phenomena
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to produce cutting-edge research. Prospective applicants must: Hold a good honours degree in an appropriate subject (including Computer Science, Physics, Maths, Engineering) Knowledge of modern machine