Frank Noé holds a Bachelor in Electrical Engineering (BA Stuttgart, funded by Robert Bosch GmbH) and a Master in Computer Science (Cork Institute of Technology, Ireland). After a brief detour in an AI startup in Frankfurt am Main, where he was developing robust Multi-Agent Systems, he pursued a PhD at the Interdisciplinary Center of Scientific Computing at University of Heidelberg (Dissertation 2006 with Jeremy
Smith and Gerhard Reinelt). In his PhD he developed continuous and discrete optimization methods for solving problems in molecular physics and biochemistry. In 2007, Frank came to Freie Universität Berlin as an independent group leader in the Applied Mathematics research center MATHEON, focusing on the development of computational statistics and shallow learning methods for molecular physics applicaitons. In 2013, he received was promoted to tenured associate Professor, in 2020 to full professor. Frank's main appoinment is in Mathematics and Computer Science at FU Berlin, and he holds appointment in Physics (FU Berlin) and an adjunct professorship in Chemistry at Rice University, Houston, Texas. In the recent years, Frank's work focuses on the interface of Machine Learning and the Physical Sciences.
Frank has received the ERC starting grant (2012), the ERC consolidator grant (2018), and the early-career award in theoretical Chemistry from the American Chemical Society (2019). In 2019 he was awarded a Simons Fellowship at the Institute of Pure and Applied Mathematics (IPAM) at University of California, Los Angeles in his capacity of organizing the IPAM long-time program on Machine Learning for Physics. In 2019 he became ISI Highly Cited Researcher.