Postdoctoral Researcher in Human-AI Intrinsic Reward

University of Oxford - Department of Experimental Psychology

Location: Department of Experimental Psychology, The Life and Mind Building, South Parks Road

The University of Oxford is a stimulating work environment which enjoys an international reputation as a world-class centre of excellence. Our research plays a key role in tackling many global challenges, from reducing our carbon emissions to developing vaccines during a pandemic.

The Department of Experimental Psychology is a large, internationally recognised department with a high volume of academic activity and a fast-paced, research-driven culture. The Life and Mind building offers renewed commitment to work across disciplinary boundaries to further knowledge across the psychological and biological sciences and to solve major global challenges.

Reporting to Professor Christopher Summerfield, we are seeking a highly talented and motivated researcher with responsibility for carrying out rigorous and impactful research into intrinsic motivation, with a particular focus on building computational theories that predict human behaviour in the absence of extrinsic rewards, and testing them using empirical studies of human behaviour.

The post is full-time and funded for two years in the first instance, with the possibility of renewal.

The post-holder will have responsibility for designing and building computational models of human intrinsic motivation and testing computational models using empirical methods online or in-lab testing of human behaviour. They will independently manage their academic and associated administrative responsibilities and provide guidance relating to computational or experimental methods to less experienced members of the research group, participate in the dissemination of research outputs, and carry out collaborative projects with colleagues in partner institutions, and research groups.

The successful candidate will have completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying human behaviour, including the use of computational models, in the context of human motivation, learning, decision-making, or a related area. Advanced programming and statistical skills with the ability to manage multiple competing demands along with excellent communication skills are also required, along with a proven track record of publishing work as lead author. Experience with machine learning methods for modelling human learning, such as knowledge tracing and/or experience with conducting research that involves prompting or fine-tuning of large language models (LLMs) would be an advantage.

The closing date for applications is 12.00 midday on 4th March 2026 and only applications received by this date will be considered.

Applications for this vacancy are to be made online. You will be required to upload a supporting statement detailing how you meet the selection criteria, your CV, and the contact details of two referees as part of your application. For further details please refer to the “How to apply” section of the job description. Click the 'Apply' button above.

Job Ref: 184558