Qualification Type: | PhD |
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Location: | Manchester |
Funding for: | UK Students |
Funding amount: | Tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid |
Hours: | Full Time |
Placed On: | 8th July 2025 |
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Closes: | 30th July 2025 |
This 4-year PhD programme is fully funded for home students; the successful candidates will receive a tax free stipend based on the UKVI rate (£20,780 for 2025/26) and tuition fees will be paid. The start date is October 2025.
Are you passionate about applying computational science to real-world engineering problems? Do you want to develop digital twins of materials that can predict performance and failure before components are built?
We invite applications for a fully funded PhD project to develop microstructure-aware simulation models for fatigue and damage prediction in turbine wheels. Working in collaboration with Cummins, a global leader in power technologies, you will contribute to the development of new generations of high-performance components for automotive and energy applications.
This research sits at the cutting edge of materials science and solid mechanics, using real-world microstructure data to simulate thermo-mechanical behaviour at the grain scale. Your work will form a key part of a larger effort to map material performance limits and unlock untapped robustness in engineering alloys.
You will:
You will also benefit from access to world-class experimental and computational facilities and participate in a cross-institutional, interdisciplinary research environment.
Applicants should have or expect to obtain a First or strong Upper Second-Class degree in Mechanical Engineering, Materials Science, Physics, or a related discipline. A background in computational mechanics, materials modelling, or engineering mathematics is essential. Prior experience with simulation tools or microstructural modelling is desirable.
To apply, please contact the supervisor, Prof Andrey Jivkov - andrey.jivkov@manchester.ac.uk. Please include details of your current level of study, academic background and any relevant experience and include a paragraph about your motivation to study this PhD project.
Deadline: 30.07.2025
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