Academic ConnectResearch Assistant / Research Associate in AI for Science - Multiple Positions (Fixed Term)
Research Assistant / Research Associate in AI for Science - Multiple Positions (Fixed Term)
We invite applications for multiple Research Assistant / Research Associate positions at the University of Cambridge to join the Molecular Engineering group in the Department of Physics, Cavendish Laboratory. Successful candidates will contribute to a short-term sprint research project that contributes directly to delivering the UK's new AI for Science Strategy developed by the Department for Science, Innovation and Technology (DSIT).
The overarching project is entitled: AI for Science: Delivering Materials 4.0 in the UK. This short-term sprint research project will focus on developing new AI for Science capabilities on the topic: Building Polymer and Battery Ontologies, Datasets and LLMs from Scientific Literature. Successful candidates will be part of a team effort to deliver a linked-research project; although each team member will focus on one or more of the individual project streams:
- Auto-generating a question-answering (QA) dataset for polymers
- Creating a domain-specific language model for polymeric science
- Auto-generating a question-answering (QA) dataset for battery devices
- Creating a domain-specific language model for battery device technology
- Creating a QA dataset for polymer nanocomposites
- Creating a domain-specific language model for wind-turbine technology
- Developing a Materials 4.0 chatbot that auto-generates material ontologies
- Building application programming interfaces (APIs) for a database platform
- Conducting archival research that delivers a professional report on the availability and opportunities for dark and grey data for polymers
- Conducting archival research that delivers a professional report on the availability and opportunities for dark and grey data for batteries
Each of the first eight project streams offer a great opportunity for a physical scientist or engineer with strong python coding skills and a keen interest in data science.
Either of the last two project streams could also suit a social scientist with strong archival and writing skills that deliver a professional business report from a literature-review study. Candidates with proven skills in delivering strong research dissertations will be particularly suited to the work of these two last streams.
Successful candidates will be expected to produce research of the highest academic quality, that they will make publication ready, and participate actively in regular project team meetings that constitute an interdisciplinary collaboration in AI for Science.
Due to the short-term nature of this project, we are unable to sponsor candidates who do not currently have a Right To Work in the UK. Postholders may work remotely in the UK or in person.
Applicants for the first eight project streams should have submitted or graduated from a research-focused undergraduate or PhD degree that specialised in a code-heavy research topic within the physical sciences, computer science, mathematics or a closely related discipline. Prior experience in AI for Materials and/or data science is advantageous but not required; a genuine interest in interdisciplinary research and working with complex, real-world datasets is important.
Applications for the last two project streams should have submitted or graduated from a research-focused undergraduate or PhD degree that delivered an academic dissertation from archival research. Ideal candidates will have undertaken such studies on data science and/or scientific policy, although this is not a requirement.
The position is fixed-term that ends on 31 March 2026. The positions are available immediately. Interviews will be held as soon as possible after the closing date.
Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.
Please submit a full curriculum vitae, a short covering letter that explains your interest in and relevant experience for one of the roles, and provide the contact details of two academic referees that are contactable at any point in the process.
Please quote reference KA48404 on your application and in any correspondence about this vacancy.
The 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.
Key information
Department/location
Salary
£33,002 - £35,608 or £37,694 - £46,049
Reference
KA48404
Category
Date published
22 December 2025
Closing date
4 January 2026
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