A 4-year fully-funded PhD studentship with Prof Mark Humphries and Dr JeYoung Yung at the University Of Nottingham is available to start September 2024. “Optimising patient selection for Deep Brain Stimulation in Parkinson’s disease using multimodal machine learning” Parkinson’s disease has debilitating motor symptoms of tremor in the limbs, slowness of movement, and freezing, unable to move. A highly effective treatment is electrical stimulation deep in the motor regions of the midbrain. But surgery for this deep brain stimulation is only offered to around 2% of all patients, and about a quarter of those who receive it have poor outcomes. Optimising the selection of patients for deep brain stimulation will widen access to treatment, improve treatment outcomes, and prevent harm. The goal of this project is to test how fusing clinical data, neuroimaging, and video assessments could optimise the selection of patients. The project will be in collaboration with MachineMedicine (London), a MedTech company specialising in Parkinson’s disease, and the movement disorders clinical team at St George’s Hospital, London. In joining this collaboration, the PhD student will be trained in data-science and machine learning tools, including how to extract and analyse MRI and fMRI data, in fusing data across modalities, and in developing a machine-learning pipeline for predicting patient outcomes. These predictions will be tested against the 12-month follow-up data from the St George’s trial patients. The student’s further training will include a 3-month placement at MachineMedicine, and visits to St George’s clinic. Closing date:12 noon (GMT) Friday 12th January 2024. For full studentship details and how to apply see here: https://more.bham.ac.uk/mrc-aim/phd-opportunities/ Send all enquires to mark.humphries@nottingham.ac.uk<mailto:mark.humphries@nottingham.ac.uk> This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please contact the sender and delete the email and attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. Email communications with the University of Nottingham may be monitored where permitted by law.