AI informed surrogate laser-material thermal models based on high-fidelity multi-physics modelling and test data

About the Project

The modelling of laser-material interactions is a complex multi-physics problem, very computationally intensive and often relies on detailed and expensive characterisation of the material's thermo-physical properties. This makes this type of analysis inaccessible for industrial applications that can require a wide range of modelling parameters, over large spatial and temporal spaces and where inputs are stochastic in nature. This is exacerbated in industrial applications that may include metals, ceramics and composite materials that require different physical modelling techniques.

The primary aim of the proposed research project is to create novel surrogate/reduced-order laser-material thermal models based on high-fidelity modelling and test data for both metals and thermo-set composite materials. To achieve this we will explore the use of advanced genetic algorithms and/or Artificial Intelligence (AI) methods that will also be applied to assess key material inputs for a range of problems of interest. Multiscale X-ray imaging from the Diamond Light Source Synchrotron facilities will be used to guide both detailed model validation as well as algorithms to determine key material data required by modelling.

Eligibility

Applicants should have, or expect to achieve, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Successful candidates will be required to undertake Baseline Personnel Security Standard checks and potentially undergo Security Clearance.

Funding

This 3.5-year PhD project is fully funded and home students are eligible to apply. This project is jointly funded by MBDA and will be undertaken in partnership. The successful candidate will receive an annual tax-free stipend set at the UKRI rate (£20,780 for 2025/26) and tuition fees will be paid. We expect the stipend to increase each year. The start date is October 2026.

We recommend that you apply early as the advert may be removed before the deadline.

Before you apply

We strongly recommend that you contact the supervisors for this project before you apply. 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.

How to apply

Apply online through our website: https://uom.link/pgr-apply-2425

When applying, you’ll need to specify the full name of this project, the name of your supervisor, if you already having funding or if you wish to be considered for available funding through the university, details of your previous study, and names and contact details of two referees.

Your application will not be processed without all of the required documents submitted at the time of application, and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered.

After you have applied you will be asked to upload the following supporting documents:

• Final Transcript and certificates of all awarded university level qualifications
• Interim Transcript of any university level qualifications in progress
• CV
• Supporting statement: A one or two page statement outlining your motivation to pursue postgraduate research and why you want to undertake postgraduate research at Manchester, any relevant research or work experience, the key findings of your previous research experience, and techniques and skills you’ve developed. (This is mandatory for all applicants and the application will be put on hold without it).
• Contact details for two referees (please make sure that the contact email you provide is an official university/work email address as we may need to verify the reference)
• English Language certificate (if applicable)

If you have any questions about making an application, please contact our admissions team by emailing FSE.doctoralacademy.admissions@manchester.ac.uk.