Jonathan Schmidt

Dr. Jonathan Schmidt is a Lecturer at the Department of Materials, ETH Zurich. His research focuses on computational materials science, integrating machine learning and high-throughput methods to predict material properties, design novel materials, and advance electronic structure theory. He specializes in quantum critical phenomena, superconductivity, and the development of open-source tools for materials discovery.

Key research areas include symmetry-based material design, density functional theory corrections, and the OPTIMADE API for data exchange. His work bridges machine learning with traditional computational methods to address challenges in phase stability prediction, electronic band structure analysis, and high-throughput screening.

Dr. Schmidt collaborates on interdisciplinary projects involving crystallography, thermodynamics, and advanced software frameworks like Atomate2. His contributions aim to accelerate materials innovation through automated workflows and data-driven approaches.