PhD Studentship: Digital Twins of Microstructure: Predictive Modelling of Fatigue in Turbine Wheels

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:

• Develop and implement physics-based microstructural models to simulate damage and fatigue
• Use experimental data on grain orientation, defect density, and residual stress to inform and validate models
• Identify critical microstructural features that govern fatigue life
• Propose optimisation strategies for turbine wheel design
• Collaborate closely with an experimental PhD student and industrial researchers
• This is a rare opportunity to lead innovation at the interface of materials, mechanics, and computation, with potential links to hydrogen engine research and broader digital twin technologies.
• You will gain expertise in:
• Computational modelling of materials (e.g., FEM, crystal plasticity, or phase-field methods)
• Multiscale mechanics and microstructure-property relationships
• Python/C++/Matlab-based simulation and data analysis
• Industry-facing research and technology transfer

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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