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Katie Atkinson

Professor at Department of Chemistry

University of Liverpool

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United Kingdom

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Research Interests

Physical Chemistry

10%

Chemistry

20%

Automation

20%

Physics

20%

Structural Chemistry

20%

Materials Science

20%

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Positions2

Publisher
source

Matthew Rosseinsky

University Name
.

University of Liverpool

PhD: Discovering New Materials in the Laboratory with Automated Reasoning and Explainable AI

This PhD project at the University of Liverpool offers an exciting opportunity to accelerate the discovery of new materials by combining explainable artificial intelligence (AI) and robotic solid-state synthesis. The research is based in the EPSRC Centre for Doctoral Training in Digital and Automated Materials Chemistry, located at the Materials Innovation Factory—the largest industry-academia colocation in UK physical science. New properties in technology require new material structures, and this project aims to discover such materials by leveraging chemical understanding and advanced computational tools. The student will use automated reasoning and explainable AI methods, recently developed by the supervisory team, to identify promising regions of chemical space for synthesis. These predictions will be explored using a robotic workflow for solid-state chemistry, integrating automated weighing, mixing, high-temperature furnaces, and AI-driven diffraction data analysis. The project is highly interdisciplinary, combining expertise in inorganic materials discovery, synthesis, and characterisation (Prof Matthew Rosseinsky) with interpretable AI tools applied to chemistry and beyond (Prof Katie Atkinson). The student will develop skills in automation, programming (including using and extending explainable AI frameworks), solid-state synthesis, crystallography, and measurement techniques. Training will also cover teamwork, scientific communication, and interdisciplinary collaboration, as computational and experimental researchers work closely together. The research builds on a new materials family recently discovered in Liverpool, notable for its structural complexity and cubic symmetry. The project offers immersion in explainable AI methods, which are essential for advancing out-of-distribution materials discovery. The student will join a team with a proven track record of integrating synthetic chemistry, computation, and AI to discover new functional materials, providing an excellent training environment. Funding is provided through the EPSRC DAMC CDT Studentship, covering full home tuition fees and a maintenance grant for four years (2025-26 rates: £5,006 pa tuition fees, £20,780 pa maintenance grant; 2026-27 rates TBC). A Research Training Support Grant is included for consumables and conference attendance. While EPSRC funding does not cover international fees, limited scholarships are available for outstanding international students to meet the fee difference. Disabled Students’ Allowance may be available for eligible candidates. Applicants should have or expect to obtain a first or upper second class degree (or equivalent) in Chemistry, Materials Science, Physics, Computer Science, or a related discipline. Experience or interest in automation, programming, solid-state synthesis, crystallography, or AI is desirable. The University of Liverpool is committed to diversity and inclusion, supporting reasonable project adaptations for students with caring responsibilities, disabilities, or other personal circumstances. The project is expected to start in October 2026. Interested candidates are encouraged to contact the supervisory team for further information and to review the CDT guide on 'How to Apply.' Applications should be submitted online, indicating Chemistry as the subject area and including the project title and reference number CCPR168. Early application is recommended, as the position will remain open until filled.

1 month ago

Publisher
source

Matthew Rosseinsky

University Name
.

University of Liverpool

PhD: Discovering New Materials in the Laboratory with Automated Reasoning and Explainable AI

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.

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