Applications are invited for a Research Assistant (pre‑doctoral) or Research Associate (post‑doctoral) to conduct world‑leading research on Leveraging Ontological Knowledge with Argumentative Agentic AI to Accelerate Chemical Development under the direction of Prof Alexei Lapkin.
The project is a collaboration with Prof Francesca Toni from Imperial College London, Dr Antonio Rago from Kings College London and industrial collaborators within the AIChemy Hub. The successful candidate will focus on extending the ontological knowledge base of chemical process development and extending the simulation environment of process models, recently developed in the group of Prof. Lapkin based in Cambridge and in Singapore.
The successful candidate will contribute to the development of reinforcement learning agents operating with the knowledge base and the simulation environment. The developed knowledge base will provide data for advanced argumentative agentic AI based on reinforcement learning being developed at Imperial College London and Kings College. The project will develop an approach of including ontological knowledge base and expert knowledge within a multi‑agentic AI framework.
The post is based in the Department of Chemical Engineering and Biotechnology at the University of Cambridge. The successful applicant will join the Sustainable Reaction Engineering (SRE) research group, led by Prof Lapkin, which works on many aspects of the transition toward sustainable chemistry, including digital transformation of R&D and manufacturing.
The successful applicant will need to interact and collaborate with other partners from Imperial College London, Kings College London and industry, as well as engage with members of the AIchemy Hub, who have expertise in AI and/or chemistry.
Duties and responsibilities
The postholder will be responsible for researching, shaping and delivering solutions based on chemical and process ontologies, the concept of knowledge graphs, simulation of models within a Python environment, working in a cloud computing environment, and will be expected to submit publications to top‑tier conferences and journals in Chemistry, Chemical Engineering and AI.
Qualifications
To apply for this position, you must have a strong background in chemical reaction engineering with a focus on first‑principles models and simulation using Python, and have experience in machine learning, for example, reinforcement learning, 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: process modelling and simulation, machine learning, reinforcement learning, ontologies. You should also have:
* A Master's degree (Research Assistant) or PhD degree (Research Associate) in chemical engineering or a related area.
* Familiarity with advanced process modelling and simulation using first‑principles models.
* Familiarity with machine learning, coding in Python.
* Excellent communication skills and ability to work with others.
* Ability to organise your own work and set priorities to meet deadlines.
* Willingness to travel to conferences and meetings of the project and of the AIChemy Hubs.
Benefits and other information
Appointment at Research Associate level is dependent on having a PhD; those without a PhD will be appointed at Research Assistant level. Fixed‑term: The funds for this post are available for 2 years in the first instance.
University actively supports equality, diversity and inclusion and encourages applications from all sections of society. The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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