Mental health problems affect around 40% of young people, making this one of today’s most urgent public health challenges. University students share many of the same difficulties as their peers but face additional academic, financial, and institutional pressures. UK policy now expects universities to adopt a “whole university” approach—addressing not only individual vulnerabilities but also the cultural and structural drivers of poor mental health. Yet the evidence to guide such systemic change remains limited.
This interdisciplinary PhD offers a unique opportunity to link rich individual-level data from the King’s Wellbeing Survey (c. 4,000 students annually) with institutional records such as academic extensions and support-for-study cases. This combination will allow the student to analyse how mental health trajectories unfold over time, how inequalities persist, and how university environments shape outcomes. Going further, the project will apply clustering and simulation approaches from physics to develop a “digital twin” of the university ecosystem. This model will enable predictive analytics and scenario testing — providing a novel tool to explore how changes to institutional practices could improve wellbeing.
The student will gain advanced training in quantitative analysis, systems modelling, and digital twin methodology, alongside qualitative interviewing and participatory methods. They will co-produce findings with a student steering group and work closely with King’s Student Services, ensuring real-world impact. This project is ideally suited to an ambitious candidate interested in combining data science, mental health research, and public health to generate actionable insights for universities across the UK.