Primary Supervisor – Dr Jacob Newman This project will focus on developing computer software and algorithms for movement activity discovery using a large, pre-existing dataset of unlabelled eye- and head-movement data obtained from healthy volunteers. You will explore ways of clustering, analysing, classifying, and representing the activities undertaken by individuals during their daily lives. This may involve the application and development of time-series clustering techniques, neural network classifiers and hidden Markov models. Such records of activities could provide clinicians with the high-level context of how disease impacts daily life, uncover what provokes changes in symptom severity, and could enable the impact of treatments to be monitored. Funding Details Additional Funding Information This PhD project is in a competition for a Faculty of Science funded studentship. Funding is available to UK applicants and comprises ‘home’ tuition fees and an annual stipend of £19,237 (for a maximum 3 years) Closing Date: 27 November 2024 (at 11.59 pm)