Explaining Structure-property Relations in the Materials Space

The definition of `isostructural' crystals remained incomplete in the IUCr dictionary until a crystal structure was defined as a rigid class of all crystal representations that can be matched by rigid motion [1]. The resulting continuous space of all periodic structures was parametrised by generically complete invariants [2] that distinguish all non-duplicate periodic materials in the Cambridge Structural Database and can be inverted to any generic 3D structure [3]. These invariants predicted a new material by structural analogy [4] and achieved state-of-the-art results in materials property prediction [5]. While past approaches often used black-box predictions, this project requires mathematical and computational skills to explain functional properties such as structural energy, gas adsorption or potential for photocatalysis in terms of the developed ultra-fast invariants [1-5]. Any property can be visualised as a mountainous landscape on geographic-style maps obtained by projecting the materials space to analytic invariant coordinates. Local optima on such landscapes will indicate the regions where target properties can be improved by modifying crystal structures in an optimal way.

This project will supervised by Prof Vitaliy Kurlin (Dept. Computer Science) and Prof Andy Cooper (Dept. Chemistry). Any informal enquiries about the project can be directed to Vitaliy.Kurlin@liverpool.ac.uk.

The global need for researchers with capabilities in materials chemistry, digital intelligence and automation is intensifying because of the growing challenge posed by Net Zero and the need for high-performance materials across multiple sectors. The disruptive nature of recent advances in artificial intelligence (AI), robotics, and emerging quantum computing offers timely and exciting opportunities for PhD graduates with these skills to make a transformative impact on both R&D and society more broadly.

The University of Liverpool EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry is therefore offering multiple studentships for students from backgrounds spanning the physical and computer sciences to start in October 2025. These students will develop core expertise in robotic, digital, chemical and physical thinking, which they will apply in their domain-specific research in materials design, discovery and processing. By working with each other and benefiting from a tailored training programme they will become both leaders and fully participating team players, aware of the best practices in inclusive and diverse R&D environments.

This training is based on our decade-long development of shared language and student supervision between the physical, engineering and computer sciences, and takes place in the Materials Innovation Factory (MIF), the largest industry-academia colocation in UK physical science. The training content has been co-developed with 35 industrial partners and is designed to generate flexible, employable, enterprising researchers who can communicate across domains.

Applicant Eligibility

Candidates will have, or be due to obtain, a Master’s Degree or equivalent related to Physical Science, Engineering or Computational Science. Exceptional candidates with a First Class Bachelor’s Degree in an appropriate field will also be considered.

Application Process

Applicants are advised to apply as soon as possible no later than 17^th February 2025. The CDT will hold two rounds of applications assessment:

·      Assessment Round 1: for all applications received between 11^th December 2024 – 15^th January 2025.

·      Assessment Round 2: for all applications received between 16^th January 2025 – 17^th February 2025

Applicants who wish to be considered in Assessment Round 1 must apply by 15^th January 2025. Projects will be closed when suitable candidate has been identified (this could be before the 17th February 2025 deadline).

Please review our guide on “How to Apply” carefully and complete the online postgraduate research application form to apply for this PhD project in Computer Science.

We strongly encourage candidates to get in touch with the supervisory team to get a better idea of the project.

We want all our Staff and Students to feel that Liverpool is an inclusive and welcoming environment that actively celebrates and encourages diversity. We are committed to working with students to make all reasonable project adaptations including supporting those with caring responsibilities, disabilities or other personal circumstances. For example, if you have a disability you may be entitled to a Disabled Students Allowance on top of your studentship to help cover the costs of any additional support that a person studying for a doctorate might need as a result.