Available
Project number:
2025_20
Start date:
October 2025
Project themes:
Main supervisor:
Lecturer in Digital Health Sciences
Co-supervisor:
Dr Alex Dregan - Reader in Psychiatric Epidemiology
Additional Information:
Developing an AI-informed risk prediction model of the relationship between suicide, comorbidity, medication, and gambling-related suicide risk: A comparative study between Armed Forces and civilian populations
Suicide is a leading cause of death globally, with Armed Forces personnel facing unique risk factors due to their exposure to high-stress environments. Mental health comorbidities such as anxiety, depression, and post-traumatic stress disorder (PTSD) are well-known contributors to suicide risk. Emerging evidence suggests that gambling-related disorders further elevate the risk of suicide, particularly among military populations. However, the relationship between these factors remains poorly understood, necessitating targeted research.
This project aims to investigate the interplay between suicide, mental health comorbidities, medication adherence, and gambling-related suicide risk by leveraging data from the Clinical Practice Research Datalink (CPRD). Using advanced data science techniques, this study will develop an AI-powered risk prediction framework to identify individuals at high risk of suicide. Machine learning models will be employed to analyse healthcare data, including mental health records and medication histories, with a focus on comparing Armed Forces personnel and civilian populations.
In addition to risk modelling, the project will explore healthcare resource use among high-risk individuals, identifying gaps in service provision and opportunities for early intervention. By analysing patterns of resource use, comorbidity, and gambling-related harms, the findings will inform more effective suicide prevention strategies tailored to both military and civilian healthcare systems.
This research will offer actionable insights for healthcare providers and policymakers, aiming to reduce suicide rates through targeted interventions, while contributing to the broader understanding of gambling-related harms as a public health issue.
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at