Julija Zavadlav

Prof. Zavadlav is an Associate Professor for Multiscale Modeling of Fluid Materials at the Technical University of Munich. She obtained her Ph.D. in physics at the University of Ljubljana in 2015. She joined ETH Zurich in 2016 for her postdoc and received an ETH Postdoctoral Fellowship award a year later. She was appointed Assistant Professor at TUM in 2019 and tenured in 2025. She was awarded the ERC starting grant and serves as a Board Member of the Atomistic Modeling Center at TUM. Her research area combines molecular modeling, multiscale simulations, and machine learning applied to complex phenomena ranging from life sciences to engineering. 

Research projects: The group of Prof. Zavadlav aims to advance bottom-up material design in various scientific fields, ranging from supramolecular peptide materials for medicinal applications to alloy design for additive manufacturing and metal-organic frameworks for electrocatalysis. To this end, the group is developing cutting-edge methods for molecular simulations, including Machine Learning-augmented molecular dynamics, multiscale modeling and simulations, Bayesian uncertainty quantification, active learning, and generative AI. Prospective students will work at the crossroads between computational physics/chemistry, machine learning, engineering, and high-performance computing.