This PhD project at the University of Liverpool offers a unique opportunity to accelerate the discovery of new materials by combining explainable artificial intelligence (AI) and robotic solid-state synthesis. The research focuses on synthesising materials with novel crystal structures, targeting promising chemical spaces guided by advanced automated reasoning tools developed by the supervisory team. You will gain hands-on experience in automation, programming, solid-state synthesis, and crystallography, working within an interdisciplinary team that integrates computational and experimental expertise.

The project is based on a recently discovered materials family in Liverpool, notable for its structural complexity and cubic symmetry. The use of explainable AI methods is essential for exploring out-of-distribution materials, enabling human researchers to build on these discoveries. The team’s expertise in interpretable AI and digital workflows provides an immersive environment for learning and innovation.

Supervised by Professor Matthew Rosseinsky (inorganic materials discovery, synthesis, and characterisation) and Professor Katie Atkinson (interpretable AI tools applied to chemistry), with support from Dr. T Manning, you will benefit from a proven track record of integrating synthetic chemistry, computation, and AI to discover new functional materials. The Materials Innovation Factory, the largest industry-academia colocation in UK physical science, offers state-of-the-art facilities and collaborative opportunities with 35 industrial partners.

The EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry (DAMC CDT) provides comprehensive training in robotic, digital, chemical, and physical thinking. The studentship covers full home tuition fees and a maintenance grant for four years, with additional support for research consumables and conference attendance. Outstanding international students may be eligible for scholarships to cover the fee difference, and candidates with disabilities may access additional support through the Disabled Students’ Allowance.

Applicants should have a strong academic background in Chemistry, Materials Science, Computer Science, Physics, or related fields, with an interest in automation, programming, solid-state synthesis, crystallography, or AI. The project encourages diversity and inclusivity, offering reasonable adaptations for students with caring responsibilities, disabilities, or other personal circumstances.

Applications are reviewed on a rolling basis and the position will be filled as soon as a suitable candidate is found. Early application is strongly recommended. For informal enquiries, contact Dr. Vikki Berryman ([email protected]). Please ensure you include the project title and reference number CCPR168 when applying, indicating Chemistry as the subject area. Review the CDT guide on 'How to Apply' for specific instructions.

References supporting the project include recent publications in Angewandte Chemie, Science, and Accounts of Chemical Research, highlighting the innovative approaches and successful outcomes of the supervisory team.