Erik Post is a PhD candidate at the AI for Parkinson Lab. His PhD focuses on the development of digital progression biomarkers for people with Parkinson’s disease. Under supervision of Luc Evers, Twan van Laarhoven, Tom Heskes and Bas Bloem, Erik explores the potential of machine learning applied to inertial measurement unit data as a means to find and quantify arm swing during gait in free-living conditions.

Prior to his PhD project, Erik obtained a Bachelor’s degree in Econometrics from the Rijksuniversiteit Groningen and a Master’s degree in Data Science & Entrepreneurship from the Jheronimus Academy of Data Science. For his thesis, he researched cardiovascular risk in the general Dutch population using machine learning-driven survival analysis in collaboration with LUMC and Pacmed.

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