PhD in Applied Mathematics

The CMR Zurich group at the Institute for Biomedical Engineering develops Magnetic Resonance (MR) technology and methods to assess the cardiovascular system. /nWe devise the next generation of diagnostic tools for quantification of blood flow, organ perfusion, metabolism and function, tissue composition, microstructure and mechanics. /nThe group exploits principles from physics, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. /nCardiovascular Magnetic Resonance (CMR) plays a central role in the non-invasive assessment of cardiac anatomy, function, and blood flow. /nHowever, long acquisition, reconstruction and data processing times continue to limit its clinical reach and robustness. /nRecent advances in machine learning, particularly deep learning and physics-informed methods, offer transformative opportunities to redesign how data are acquired and reconstructed, and how physiological parameters are inferred from the data. /nThis PhD project focuses on developing learning-based strategies for accelerated data acquisition, physics-informed image reconstruction, and quantitative inference of cardiovascular anatomy and hemodynamics. /nThe research will integrate modern machine learning with MR signal modeling, computational imaging, and fluidmechanis, with the ultimate goal of enabling faster, more reliable, and more informative CMR. /nThe project will be carried out in a highly interdisciplinary environment at ETH Zurich, with close collaboration between engineers, physicists, clinicians, and data scientists, and access to state-of-the-art imaging infrastructure and clinical datasets.