Loughborough University
About the Project
Machine learning techniques are increasingly being applied to materials science, particularly in the modelling of complex materials. Traditional methods like Density Functional Theory (DFT) provide chemically accurate results but are computationally expensive. On the other hand, cheaper methods often lack the chemical detail required for high-precision simulations. Machine learning offers a solution by using large datasets of accurate DFT calculations to train models that are faster while maintaining essential chemical accuracy.
This project focuses on applying these machine learning techniques to model bulk carbon materials, specifically synthetic graphite. Synthetic graphite is used extensively in nuclear reactors, including both current reactors in the UK and the next generation of planned reactors. Understanding the behaviour of graphite under the high-temperature, high-irradiation conditions in reactor cores is crucial for improving reactor design and the clean-up and recycling of irradiated graphite.
Graphite bricks in nuclear reactors experience expansion and contraction over time, which can lead to cracking—a potential safety hazard. This project aims to develop computational models to better understand the causes of graphite swelling, particularly the impact of single-atom defects and larger structural deformations (such as ripples and folds) in the graphene sheets.
The goal is to develop AI-based force-field models that can accurately simulate graphite under both low-energy bonding conditions and the high-energy collisions caused by radiation damage. This will involve creating a hybrid model that combines the strengths of existing models, tailored specifically for simulating irradiated graphite. As part of the project, we will explore new machine learning and AI techniques to predict atomic dynamics within carbon materials.
PhD Opportunity:
We are looking for a motivated and enthusiastic PhD candidate to join our research group, which is based in the Department of Chemistry. The team includes a post-doctoral researcher and undergraduate project students. You will have the opportunity to actively engage in weekly group meetings, where you can present your findings, propose new ideas, and collaborate with others. EDF is an advisory partner on this project, providing further opportunities for collaboration and interaction.
This project offers an excellent opportunity for developing a wide range of skills, including:
- Computer programming and simulation techniques
- Conducting large-scale simulations on high-performance computing systems
- Data analysis using Python, C++, or similar languages
- Writing and typesetting academic papers and reports using LaTeX
This is a unique chance to contribute to cutting-edge research in materials science and nuclear technology, while gaining valuable experience in both theoretical and computational aspects of the field.
The school of science also has good policies in place on flexible working, maternity/parental leave, and Loughborough University and the School are involved with Athena Swan, the Race Equality Charter, Disability Confident Employer and Stonewall Diversity Champion statuses.
94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021
Supervisors
- Primary supervisor: [email protected]
Entry requirements
Students should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in Mathematics, Physics, Computer Science, or a related subject.
English language requirements
Applicants must meet the minimum English language requirements. Further details are available on the International website.
Start date
April 2025, July 2025, October 2025
Tuition fees for 2024-25 entry
- UK fee – £4,786 Full-time degree per annum
- International fee – £27,500 Full-time degree per annum
Tuition fees for 2025-26 entry
- UK fee – To be confirmed Full-time degree per annum
- International fee – £28,600 Full-time degree per annum
Fees for the 2024-25 academic year apply to projects starting in October 2024, January 2025, April 2025 and July 2025.
Fees for the 2025-26 academic year apply to projects starting in October 2025.
How to apply
All applications should be made online. Under programme name, select the school of science/ chemistry. Please quote the advertised reference number: CM/KJ-SF1/2025 in your application.
To avoid delays in processing your application, please ensure that you submit a CV and the minimum supporting documents.
The following selection criteria will be used by academic schools to help them make a decision on your application.
Please note, applications for this project are considered on an ongoing basis once submitted and the project may be withdrawn prior to the application deadline, if a suitable candidate is chosen for the project.
To help us track our recruitment effort, please indicate in your email – cover/motivation letter where (theacademicjob.com) you saw this job posting.