| Location: | London |
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| Salary: | £49,017 to £57,472 per annum |
| Hours: | Full Time |
| Contract Type: | Fixed-Term/Contract |
| Placed On: | 14th November 2025 |
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| Closes: | 10th December 2025 |
| Job Ref: | NAT02092 |
About the role:
Funded by a European Research Council Starting Grant, you would be working on the project "Defect-Tolerant Materials for Energy" at the interface of Materials Chemistry and Artificial Intelligence (AI). The project will focus on the use of computational chemistry and data-driven approaches to accelerate the discovery of inorganic materials for energy applications, including photovoltaics, transparent conductors, and thermoelectrics. This is an exciting opportunity to design and implement novel AI approaches for materials design and discovery. You will be part of a larger team of Research Associates and PhD students, consisting of computational chemists and computer scientists specialising in AI.
You will develop methods for extending machine learning force fields and training defect foundation models, using both software tools you develop and data collected by the larger team. You may also explore the potential for generative AI to accelerate the search for defect-tolerant materials. The broader research environment also includes the EPSRC-funded AI hub for Chemistry (AIchemy), for which Dr Ganose is a co-investigator.
What we are looking for
The post is ideal for individuals interested in working creatively at the intersection of AI and energy materials.
What we can offer you:
Further Information
A start date from 01 February 2026 or thereafter is available.
You will be based at White City Campus, some travel to South Kensington Campus will be required.
This is a full-time post (35 hours per week) and fixed term for 24 months.
Candidates who have not yet been officially awarded their PhD will be appointed as a Research Assistant.
If you require any further details about the role, please contact: Dr. Alex Ganose, a.ganose@imperial.ac.uk
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