Supervised by Rundong Yan, Alistair Speidel, and Rasa Remenyte-Prescott 

This exciting opportunity is based within the Resilience Engineering Research Group at Faculty of Engineering which conducts cutting edge research into developing modelling techniques to predict ways of improving the design, maintenance, and operation of engineering systems in order to reduce the frequency and consequences of failure.

Vision

We are seeking a PhD student who is motivated to rethink how manufacturing systems are designed, moving beyond forward, trial-and-error approaches towards goal-driven, performance-led system design. The student will work at the intersection of systems engineering, modelling and simulation, and data-driven methods to develop an inverse design framework for manufacturing systems.

Together, we will advance the capability to design manufacturing systems that embed reliability, resilience, adaptability, and sustainability from the outset. By scientifically linking high-level performance objectives to system architecture and design decisions, this research aims to reduce costly late-stage redesign and enable manufacturing systems that can respond effectively to changing operational conditions. The outcomes of this work will support more efficient industrial design processes and contribute to the development of future manufacturing systems that are robust, reconfigurable, and fit for long-term operation.

Motivation 

Modern manufacturing systems are required to operate under increasing uncertainty, frequent change, and competing performance demands, including reliability, resilience, adaptability, and sustainability. However, current manufacturing system design approaches largely remain forward-driven: systems are designed, analysed, and only then assessed against these performance. At the same time, manufacturing is undergoing a major transformation driven by digitalisation, reconfigurable production, and the need for more sustainable and resilient operations. These trends demand design methodologies that can explicitly account for performance goals from the outset, rather than treating them as afterthoughts. Despite advances in modelling, simulation, and data-driven optimisation, there is currently limited methodological support for systematically translating high-level performance objectives into concrete manufacturing system design decisions.

There is a clear need for new design approaches that enable engineers to reason backwards from desired system behaviour to feasible and robust system configurations across different operating environments and requirements. Addressing this gap will support the development of manufacturing systems that can better adapt to change, reduce costly redesign, and deliver sustained performance over their operational lifetime.

Aim

You will have the opportunity to develop a model-based systems engineering framework for the inverse design of manufacturing systems, enabling high-level performance objectives to directly inform system architecture and design decisions.

During the project, you will work closely with academic supervisors from both the Resilience Engineering Research Group and the Advanced Manufacturing Technology Research Group at the University of Nottingham, applying modelling, simulation, and data-driven methods to link high-level performance objectives to practical manufacturing system designs. You will develop and use advanced techniques, such as Petri nets and AI-based optimisation, to explore system behaviour and generate robust, adaptable, and sustainable manufacturing system configurations.

The project will involve applying these approaches to realistic manufacturing environments, allowing you to contribute to both methodological advances and industrially relevant case studies. This experience will prepare you for careers in advanced manufacturing, systems engineering, digital manufacturing, and research roles in academia or industry.

Who we are looking for

We are looking for an enthusiastic, self-motivated, and resourceful candidate with a strong interest in systems engineering, manufacturing systems, and modelling and simulation. You should be able to work independently as well as collaboratively, and be motivated to tackle open-ended research problems.

You should hold, or expect to obtain, a first-class or upper second-class (2:1) degree in a relevant discipline in engineering, science, or mathematics. Experience with modelling, simulation, optimisation, or programming (e.g. Python, MATLAB, C++, or similar) would be advantageous, though not essential, as learning and training will be expected during the PhD study.

Funding support

After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process. (this will cover home tuition fees and UKRI stipend).

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society

The Faculty of Engineering provides a thriving working environment for all PGRs creating a strong sense of community across research disciplines. Community and research culture is important to our PGRs and the FoE support this by working closely with our Postgraduate Research Society (PGES) and our PGR Research Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. 

For any enquiries about the project and the funding, please email Dr Rundong (Derek) Yan (rundong.yan@nottingham.ac.uk), Dr Alistair Speidel (Alistair.Speidel@nottingham.ac.uk), or Dr Rasa Remenyte-Prescott (r.remenyte-prescott@nottingham.ac.uk)

This studentship is open until filled. Early application is strongly encouraged.

Closing Date: 02 Feb 2026
Category: Studentships

This exciting opportunity is based within the Advanced Manufacturing Technology Research Group at Faculty of Engineering which conducts cutting edge research into sustainable high-value manufacturing processes.

Vision

We are looking for a PhD student who is motivated to develop the next generation of manufacturing processes alongside our partners in Rolls-Royce.

Aviation faces a dual challenge: decarbonisation and growing vulnerability in critical raw material supply chains. High-temperature aerospace components rely on exotic alloys and coatings with high embodied carbon and zero domestic supply, yet these components degrade in service.

This PhD project is driven by a vision of extending the life, performance, and value of existing aerospace assets, reducing reliance on virgin critical materials, and enabling more sustainable and circular manufacturing practices within the aerospace sector.

Motivation 

For aerospace gas turbines, most emissions occur during operation, but the materials used to manufacture critical components also carry a significant environmental and strategic burden. During service, components such as blades, guide vanes, and compressors are damaged by calcia–magnesia–alumino–silicate (CMAS) ingress, which degrades thermal barrier coatings and limits component life.

Current recoating and preventative coating methods are effective at a bulk level but struggle to preserve or restore small-scale engineered features that are essential for thermal and aerodynamic performance. This creates a strong need for precision, adaptable, and scalable reconditioning approaches that go beyond conventional manufacturing routes.

Aim

The aim of this PhD is to develop and understand non-conventional electrophysical and laser-based manufacturing processes for the restoration and remanufacturing of aerospace gas turbine components.

The project will:

• Investigate fundamental process–material interactions between coatings, substrates, and electrophysical/laser processes
• Explore process-specific phenomena (including plasma effects) to enable highly localised material removal and deposition
• Develop best-practice methodologies for restoring or enhancing small-scale functional features
• Translate findings towards scalable and deployable solutions, with miniaturised, on-wing demonstration

The research will be conducted in close collaboration with Rolls-Royce and will directly inform industrial practice in component repair and life-extension.

Who we are looking for

We are seeking a highly motivated and curious PhD candidate with a strong interest in advanced manufacturing, materials, and sustainability. You should have (or expect to obtain) a good first degree (1^st or a 2:1) in a relevant discipline, such as:

• Mechanical Engineering
• Manufacturing Engineering
• Materials Science/Metallurgy

The ideal candidate will:

• Enjoy hands-on research
• Be interested in non-conventional manufacturing processes (e.g. EDM, laser processing, coatings)
• Be motivated by industry-focused research with real-world impact
• Be comfortable working at the interface of academia and industry

You will join a supportive supervisory team spanning academic and industrial expertise, with access to specialist equipment (including EDM and laser systems) and strong links to Rolls-Royce and university spin-outs.

Please contact Alistair Speidel for further questions and to apply for this opportunity alistair.speidel@nottingham.ac.uk

Funding support

After a suitable candidate is found, funding is then sought from the University of Nottingham as part of a competitive process (this will cover home tuition fees and UKRI stipend)

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The Faculty of Engineering provides a thriving working environment for all PGRs creating a strong sense of community across research disciplines. Community and research culture is important to our PGRs and the FoE support this by working closely with our Postgraduate Research Society (PGES) and our PGR Research Group Reps to enhance the research environment for PGRs. PGRs benefit from training through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has outstanding facilities and works in partnership with leading industrial partners. 

Closing Date: 02 Feb 2026
Category: Studentships