[School of Engineering PhD Scholarships] Quantum Computing for Machining Simulation

About the project

About the Project Machining simulation is critical for selecting cutting conditions that control machining errors such as force, vibration, tool/workpiece deformation, surface location error and chatter without costly production trials. However, high-fidelity simulation requires the machining dynamics to be resolved at each point along the tool path. Repeating these calculations across the thousands of points in a typical tool path can make the overall computational cost prohibitive, forcing engineers to simplify simulations at the expense of accuracy. Quantum computing offers a fundamentally different approach to computation and may provide substantial reductions in time to solution for some large scientific problems. This project will investigate whether quantum algorithms can accelerate high-fidelity machining simulation and optimisation, enabling cutting conditions and machining strategies to be explored more rapidly and with fewer costly physical trials. The project will combine quantum computing, numerical modelling and machining dynamics. The student will develop representative milling simulations, identify computational bottlenecks and investigate quantum algorithms for solving the underlying dynamical systems. Machining tool paths will be generated using commercial and in-house software, and experiments carried out using in-house CNC machine tools equipped with relevant sensors. The longer-term aim is to use information identified during machining to improve the tool path of subsequent passes, providing a foundation for real-time tool-path optimisation in future manufacturing systems. The student will receive joint supervision from Peter Brearley and Z. Murat Kilic, combining expertise in quantum algorithms and machining dynamics. Training will cover quantum computing, numerical linear algebra, CNC machining dynamics and modelling, differential equations, stability analysis and scientific programming. The student will also benefit from the supervisors’ wider research communities and opportunities to publish and present their work. This project is expected to start in September 2027. Before you apply: We strongly recommend that you contact the supervisors for this project before you apply. How to apply: To be considered for this project you must complete a formal application through our online application portal. If you already have an applicant account this link will directly open an application for PhD School of Engineering Scholarships . If you don’t already have an applicant account, please follow the instructions here. . When applying, please specify the full title and supervisor/s of the project, details of your previous study, and names and contact details of two referees. You must also upload a Supporting Statement describing the motivation to apply to the project, your CV and transcripts of awarded and in-progress university qualifications . Please note late or incomplete applications will not be considered. Equality, diversity and inclusion are fundamental to the success of The University of Manchester and central to all our activities. A diverse research community strengthens creativity, productivity and quality, while increasing the societal and economic impact of our work. We welcome applicants from all career paths, backgrounds and sections of the community, regardless of age, disability, ethnicity, gender, gender expression, sexual orientation or transgender status. We welcome applications from candidates returning to study after a career break or experience in other roles. Flexible study arrangements may be available, including part-time study at 50%, 60% or 80%, subject to the requirements of the project and funder. Eligibility : The standard academic entry requirement for this PhD is an upper second-class (2:1) honours degree in engineering, mathematics, physics, or a related discipline (or international equivalent) OR any upper-second class (2:1) honours degree and a Master’s degree at merit in engineering, mathematics, physics, or a related discipline (or international equivalent). Strong interest and skills in numerical methods, dynamical simulations and computer programming demonstrated by previous experience (e.g. dissertation, project or course) is desirable. Prior knowledge of quantum computing or machining dynamics is not required. This project will remain open until filled. If your application is submitted by 1 st November 2026, you can expect a decision by 18 th December 2026. If your application is submitted by 15 th January 2027, you can expect a decision by 30 th March 2027. Self or externally funded students can also be considered for this project. FSESoE

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