Research Associate in AI for Chemistry at Imperial College London

The EPSRC has funded AIChemy, a research hub to develop artificial intelligence (AI) for chemistry. AIChemy seeks to both develop new AI approaches and to uptake AI into the chemistry community. The Hub brings together AI researchers from many subdisciplines and both experimental and computational chemists. The hub will promote connectivity of the broader community, training, networking, as well as state-of-the-art research.

This is an exciting opportunity to design and implement novel digital technologies in collaboration with a wide range of academic and industrial partners who will be part of AlChemy ‚Äď a new Hub involving Imperial College London, the University of Liverpool, and a large consortium of academic and industrial partners.

There are two openings for research posts at the Research Associate level, one in Generative AI for small molecules and materials, and one in multi-fidelity machine learning for Chemistry. Candidates are welcome to state their preference on which area they would prefer to work in, on their application.

This is an exciting opportunity to work within the larger team at Imperial, and across the AIChemy hub to collectively deliver novel AI for Chemistry.

You will work on projects coordinated between both experimental chemistry and machine learning academics. These posts offer the academic freedom and the deep science base of Imperial College London and University of Liverpool (including self-driving labs and high-throughput synthesis and analysis setups) to make a notable contribution to the field.

Duties and responsibilities

You will:

  • Develop new approaches for the design of promising molecules and materials that have the potential to be synthesised by experimental collaborators.
  • Apply and develop machine learning methods, Bayesian optimisation strategies, and existing computational chemistry software for the successful prediction of a range of materials, across molecular and solid-state organic and inorganic systems.
  • Explore how material performance in a range of applications can be predicted with, where possible, simple descriptors.

Essential requirements

  • Hold, or be near completion of, a PhD in Chemistry or Computer Science or a closely related discipline, or equivalent research, industrial or commercial experience
  • Current knowledge in computational chemistry, physics, or materials science
  • Current knowledge in AI, ideally for use in the chemical sciences
  • Practical experience in a state-of-the-art techniques in AI for chemistry, such as generative AI, Bayesian optimisation, and graph neural networks.
  • Experience of dealing with multidisciplinary experimental and computational collaborators
  • Practical experience within a research environment and publications in relevant and refereed journals.

Further information

This is a full time, fixed term position for two years. You will be based at White City Campus with some time spent at the South Kensington Campus, as required for the delivery of the research.

For more information and to apply visit

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