Ali Alim Marvasti

Ali Alim-Marvasti has been working in the field of neurology since 2014. Ali began their career as a Neurology Registrar (ST4/ST5) at Imperial College Healthcare NHS Trust. In 2016, they took on a role as Physiology supervisor (MVST IA Homeostasis): Nerve & Muscle at the University of Cambridge. Ali also became a Neurology Registrar (ST6) at Chelsea and Westminster Hospital NHS Foundation Trust. In 2017, they were a Neurology ST6/ST7 at University College London Hospitals NHS Foundation Trust. In 2018, they became an Honorary Consultant Neurologist at the National Hospital for Neurology and Neurosurgery, a Wellcome/EPSRC WEISS CLINICAL TRAINING FELLOW and PhD Candidate in Machine Learning for Epilepsy at UCL, and a Neurology ST7 Registrar at Imperial College Healthcare NHS Trust. In 2019, they were a Locum Consultant Neurologist at Northwick Park Hospital. In 2021, they became a Locum Consultant Neurologist at The Hillingdon Hospitals NHS Foundation Trust and a Neurology Lead & Head of Research at Mindstep.

Ali Alim-Marvasti has a long and varied educational history. Ali began their studies in 2003 at the University of Cambridge, where they earned an MB.BChir, MA(Hons) in Medical Sciences and Clinical Medicine. In 2005, they participated in a Bachelor's exchange programme at the Massachusetts Institute of Technology, studying Brain and Cognitive Sciences, Biology, Special Relativity, and fMRI. In 2012, they earned an MRCP(UK) from The Royal College of Physicians. In 2016, they earned a Specialty Certificate in Neurology from The Royal College of Physicians after taking the UK Neurology Board Exam. Ali is currently pursuing a PhD in Neuroscience at UCL, which they began in 2018 and is expected to complete in 2022. In addition to their formal education, Ali Alim-Marvasti has obtained several certifications, including Code Clinic: R (2015) from LinkedIn in 2021, Meta Analysis in R (Centre for Applied Statistics Courses) from UCL in 2020, Faster Python Code from LinkedIn in 2020, Experimental Design and Power Analysis from Responsible Research in Practice in 2020, Python: Programming Efficiently from LinkedIn in 2020, Machine Learning (Stanford) from Coursera in 2017, Python for Data Science from DataCamp in 2017, and Research Software Engineering with Python from UCL.