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About the role
This post of Research Assistant (pre-doctoral) or Research Associate (post-doctoral) is to conduct world-leading research on Leveraging Ontological Knowledge with Argumentative Agentic AI to Accelerate Chemical Development under the direction of Prof Francesca Toni, in collaboration with Prof Alexei Lapkin from the University of Cambridge, Dr Antonio Rago from King’s College London, and industrial collaborators, within the AIChemy Hub (https://aichemy.ac.uk/). The successful candidate will focus on developing an advanced argumentative agentic AI approach for chemical development settings based on reinforcement learning but able to shape rewards with the help of ontological knowledge of chemical process development (by the group of Prof. Lapkin based in Cambridge and in Singapore) as well as expert knowledge from humans and from other agents. The approach will be based on and will develop techniques from computational argumentation combined with reinforcement learning. The argumentative agents will be able to interact with other such agents using methodologies for argumentative exchanges developed at King’s College London.
The successful applicant will join the CLArg research group, led by Prof Toni. The successful applicant will need to interact and collaborate with the other partners from from the University of Cambridge, King’s College London and industry, as well as to engage with others with expertise in AI and/or chemistry.
What you would be doing:
The position offers an exciting opportunity for conducting internationally leading and impactful research in AI. The Research Assistant/Associate will be responsible for researching, shaping and delivering solutions based on argumentative agentic AI in a variety of settings (formats, models and data), and will be expected to submit publications to top-tier conferences and journals in AI as well as Chemistry and Chemical Engineering.
What we are looking for:
- A strong computer science background with a focus on AI, have experience, including a proven publication track-record, in at least two of the following areas, as well as ability and willingness to become familiar with the others: reinforcement learning, computational argumentation, multi-agent systems, ontologies.
- A Master’s degree (Research Assistant) or PhD degree (Research Associate) in computer science or a related area.
- Familiarity with standard reinforcement learning libraries/data analysis
- Excellent communication skills
- Ability to organise own work and set priorities to meet deadlines.
- Willingness to travel to conferences and meetings of the project and external collaborators.
Please see job description for a full list of requirements.
Further Information:
Full-time, Fixed term contract to start July 2026 or soon after for up to 24 months.
Candidates who have not yet been officially awarded their PhD but are in the process of obtaining one will be appointed as Research Assistant within the salary range £43,863 – £47,223 per annum.
Visit https://www.imperial.ac.uk/jobs/ and search vacancy reference ENG03872
In addition to completing the online application please attach:
- A full CV with a list of all publications
- A 2-page research statement indicatingwhat you see are interesting research issues relating to the above post and why your expertise is relevant.
Informal enquiries should be directed to Professor Francesca Toni – ft@imperial.ac.uk
For queries regarding the application process contact: j.perrins@imperial.ac.uk
Closing Date: 10th May 2026 (midnight)