Research Assistant(s) in Fundamental AI Research Part-time

Research Assistant(s) in Fundamental AI Research – Central Oxford

We are seeking two full-time Research Assistants to join the BOLD Lab at the Department of Engineering Science (central Oxford). The post is funded by EPSRC and is fixed-term for 12 months.

This is an opportunity to join The British Open-ended Learning and Discovery (BOLD) Lab, a major new UK Research and Innovation (UKRI) funded initiative that will establish a world-leading AI research laboratory at the University of Oxford. Bringing together more than 80 researchers from Oxford, UCL and Imperial under one unified vision, BOLD Lab will pursue ambitious, high-risk research to advance the fundamental science of artificial intelligence and address some of the field's most important challenges. BOLD has three initial research pillars: Beyond Backpropagation, Human-Centric Learning & Discovery, and Embodied Learning.

You will be responsible for running experiments to test deep learning models at scale, organising the results, and extracting insights in the process. In this highly collaborative role, you will be working with other researchers in the team to support BOLD's development and research portfolio and in the maintenance and development of the research code base.

You should possess a relevant first degree together with relevant experience and possess sufficient specialist knowledge in the fundamental AI research to work within established research programmes.

Informal enquiries may be addressed to boldexec-team@eng.ox.ac.uk. For more information about working at the Department, see www.eng.ox.ac.uk/about/work-with-us/. Only online applications received before midday on 9 October 2026 can be considered. You will be required to upload a covering letter/supporting statement, including a brief statement of research interests (describing how past experience and future plans fit with the advertised position), CV and the details of two referees as part of your online application.

The Department holds an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology.

• Agentic AI

• Human-AI coordination

• Zero-shot Coordination

• Multi-agent learning