Details.
Funded, full-time PhD project at the intersection of network science, machine learning and mental health research. The project will integrate and analyze multimodal data, including cognitive assessments, patient self-reports, neuroimaging and electronic health records, using natural language processing, graph theory and advanced machine learning to identify biomarkers and improve the profiling of mental health trajectories. Candidates should have a strong educational background in computer science, network science, data science, neuroscience, computational sciences, engineering or a related subject, proficiency in relevant programming languages such as Python, R, SQL, Matlab or Julia, fluency in English, strong analytical and communication skills, personal initiative, and an interest in interdisciplinary research. The scholarship covers full tuition fees, an annual stipend, an additional London allowance and associated costs for three and a half years. Applications are open to UK and international students.