I am a Senior Research Fellow in Computational Imaging Analysis, based at the Queen Square Multiple Sclerosis Centre (QSMSC), UCL. My current work is in collaboration with healthcare industry partners to develop advanced neuroimaging biomarkers for the prediction and monitoring of treatment in progressive MS, using machine learning techniques and network modelling of the brain. My wider research involves developing multilayer brain networks and applying brain network simulation models to better understand how pathology impacts cognitive function. I have extensive experience working with multimodal neuroimaging and large datasets as well as advanced statistical analysis and modelling to interrogate data. I am proficient in Matlab, R, Python and Unix/Linux systems. I have worked across several clinical populations inclusive of traumatic brain injury, dementia and neuropsychiatric conditions such as depression and obsessive compulsive disorders and have experience working within and analysing clinical trial data.I am particularly interested in data science, applying advanced statistical modelling techniques to large multimodal datasets to extrapolate information that improves our ability to understand disease mechanisms and predict treatment outcomes. I am passionate about how my work can be translated into real-world clinical use to improve the lives of others.https://profiles.ucl.ac.uk/86101-amy-jolly