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Graduate Research Assistant in Applying AI to Digital Mental Health Solutions

University of Exeter - Faculty of Health and Life Sciences

Location: Exeter, Hybrid/Remote
Salary: The starting salary will be from £33,951 on Grade E, depending on qualifications and experience.
Hours: Full Time, Part Time
Contract Type: Fixed-Term/Contract
Placed On: 6th November 2025
Closes: 20th November 2025
Job Ref: R92154

The Department of Psychology are looking to recruit a Graduate Research Assistant in AI to Digital Mental Health Solutions.

This new full-time post is available from 1 December 2025 until 1 December 2026 in the Department of Psychology.

This role can be based anywhere in the UK or it can be offered under a hybrid working arrangement - some time on campus and some from home.

We welcome applications from candidates interested in working part-time hours (minimum 0.8 FTE) or job-sharing arrangements.

About the role
We are looking for an innovative Graduate Research Assistant to pioneer the intersection of Generative AI and behavioural science, aiming to transform mental health care. You would join a team aspiring to leverage cutting-edge AI models to refine and elevate the efficiency of mental health interventions.

Our objectives are two-fold: to study how AI systems can cost-effectively optimise mental health training and support, and to harmonise AI models with human treatment delivery to produce an ethical, widely acceptable and scalable treatment model.

The PATH-AI: Psychological Advancements Through Human-AI Collaboration Group is an international group of leading mental health researchers and clinicians focussed on using technology to produce novel solutions to global mental health challenges. Our members include senior academics and researchers from Exeter, the Human Sciences Research Council (HSCR), Oxford, Bristol, UCLA, and Harvard.

Our top priorities are to:

  • Use ML/AI to characterise and evaluate models of mental health provider skill/competency and predict optimal treatment performance indicators.
  • Drive a step-change in scalable mental health provision using AI systems to create novel workforce efficiencies. We will utilise ML/AI to ensure rapid, cost-effective, high-impact workforce solutions to international gaps in specialist mental health providers.
  • Facilitate information exchange. We will share information between our established national and international channels. These include policymakers, NGO’s, international partners, private companies, and the broader public.

About you
Applicants will be educated to first degree level or possess an equivalent qualification/experience in a related field of study or equivalent experience and be able to demonstrate sufficient knowledge in the discipline and of research methods and techniques to work within established research programmes.

The post-holder will help coordinate research in this groundbreaking area, by evaluating the efficacy of AI models (especially large language models [LLMs]) in capturing the nuances of therapist competencies and predicting client treatment outcomes, using existing real-world data from mental health treatment.

Please ensure you read the Job Description and Person Specification (available on the university's website, accessed by the 'Apply' button) for full details of this role.

The University of Exeter
We are a member of the prestigious Russell Group of research-intensive universities and in the top 200 universities in the world (Times Higher Education World University Rankings 2024 and QS World University Ranking 2024). We combine world-class teaching with world-class research, achieving a gold rating in the Teaching Excellence Framework Award 2023, underpinned by gold ratings for Student Experience and Student Outcomes.

Our Equality, Diversity and Inclusion Commitment
We are committed to ensuring reasonable adjustments are available for interviews and workplaces.

Whilst all applicants will be judged on merit alone, we particularly welcome applications from groups currently underrepresented within our working community.

Further information
Please contact Professor Heather O’Mahen, H.OMahen@exeter.ac.uk.

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