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Postdoctoral Researcher: AI Safety in Mental Health

University of Oxford - Department of Psychiatry

Location: Oxford
Salary: £39,424 to £47,779 per annum. Grade 7
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 8th October 2026
Closes: 4th November 2026
Job Ref: 189155

Location: Warneford Hospital, Oxford OX3 7JX 

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 Psychiatry is based on the Warneford Hospital site in Oxford – a friendly, welcoming place of work with an international reputation for excellence. The Department has a substantial research programme, with major funding from Medical Research Council (MRC), Wellcome Trust and National Institute for Health Research (NIHR) and provides highly rated medical training in psychiatry. The Head of Department is Professor Belinda Lennox. 

We are looking for a postdoctoral researcher to work on delivering state of the art AI safety work for the ARIADNE consortium, a Wellcome Trust-funded project developing a generative artificial intelligence system that conducts clinical interviews to assess risk of psychosis. 

About the Role

The post is full-time and funded for 2 years.  It is based in the Department of Psychiatry at the Warneford Hospital. 

The post is available on flexible hybrid basis, with the minimum on-site attendance of three days per week for a full-time post. 

You will join the AI arm of the Computational and Molecular Neuroscience Laboratory. You will work closely with this group and with the wider ARIADNE team of clinicians, ethicists and lived-experience researchers across the Universities of Oxford, King's College London, Birmingham and Cambridge, working in partnership with Google DeepMind.

Your research will focus on the safety of ARIADNE ahead of clinical evaluation. You will address the two principal safety risks identified through formal risk analysis (ISO 14971): inadvertent reinforcement of delusional beliefs, and inappropriate responses to suicidal symptoms. You will develop LLM “supervisor” modules that detect these events and flag them to the debriefing clinician, and will evaluate them in controlled testbeds in which LLM-simulated patients, representing five levels of symptom severity, complete ARIADNE interviews scored at scale by independent LLM evaluators and calibrated against human clinicians.

About You

You will have or be close to the completion of PhD/DPhil in machine learning, computer science, computational neuroscience, mathematics, or a related quantitative discipline and possess sufficient specialist knowledge in the discipline to work within established research programme

You will have proven experience developing and systematically evaluating LLM-based systems, including prompt-based, agentic or multi-agent approaches, using modern Python and LLM APIs. You will also have experience designing and analysing empirical evaluations of machine-learning systems, ideally including simulation-based methods, LLM-as-judge approaches, and validation of automated evaluations against human ratings.

Experience with AI safety evaluation methods, such as red-teaming, guardrail architectures or model-based monitoring and of fine-tuning large language models with deep learning frameworks (e.g. PyTorch) or applying alignment techniques (e.g. reinforcement learning from human feedback, DPO) would be desirable.

Diversity

Committed to equality and valuing diversity, our active Psychiatry People and Culture teams and initiatives including our values and behaviours framework, work to make the Department of Psychiatry as supportive, welcoming and inclusive as possible.

Application Process

You will be required to upload a covering letter/supporting statement, CV and the details of two referees as part of your online application. Please see the University pages on the application process at https://www.jobs.ox.ac.uk/application-process

The closing date for applications is 12:00 midday on 4 November 2026

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