This student will work as an Undergraduate Research Assistant in the Magnetic Resonance Scientific Engineering for Clinical Excellence (MR-SCIENCE) Laboratory. His project will involve developing a classifier, using supervised Machine Learning techniques, which utilizes metabolite concentration data acquired from 7T MRS of Multiple Sclerosis patients, to accurately triage patients between different stages of MS and from healthy controls. He will then utilize non-supervised learning approaches to identify potential metabolite biomarkers that noticeably differentiate between the groups. The project duration will be 12 weeks over the summer.
