Up to three 4-year, fully funded ‘Joint A*STAR – EPSRC DRIVE-Health Studentships’ are available to support PhDs commencing October 2026, covering tuition fees, stipend, and bench fee.
Students recruited to these studentships must spend a minimum of 18 months and a maximum of 24 months at A*STAR Research Institute in Singapore with the named A*STAR supervisor(s) as part of the research and training programme. This is called the “attachment” period, and it will start in their second academic year.
Applications are accepted from citizens of the UK, the EU, the USA, Canada, Latin America, and Australia.
Please read the specific Key Dates and How to Apply sections on this collaboration with A*STAR. Apart from the regular DRIVE-Health entry requirements and application process, A*STAR applicants will have a 2-tier interview process: by a KCL academic panel and a panel from Singapore.
Our voices are a window into our mental health when combined with powerful artificial intelligence analyses; they contain valuable clues to how well our brain and the speech muscles it controls are working. Already, researchers have been able to assess the severity of health conditions such as depression from speech recordings made in tightly controlled conditions. In the future, the analysis of speech recorded on smartphones in everyday life could meet a large unmet need for convenient, objective tools that monitor symptom severity, increasing access to health services. However, to reliably monitor changes linked to our mental health, we first need to explore how best to develop robust and reliable machine learning models to characterise and track these changes. This project will utilise data resources collected as part of large observational trials on the use of Remote Measurement Technologies (RMT) to monitor changes in health state, for example, to assist in predicting changes in symptoms and relapse in people with major depressive disorder. The supervisory team contains expertise across the domain of speech processing and machine learning, with relevant training opportunities provided through the Department of Biostatistics and Health Informatics and King’s College London. In short, this project represents a unique chance to undertake novel research with leading experts in the field, whose outputs will represent a clear step change in the development of speech phenotype for use in healthcare and research settings.