PhD and Postdoctoral Positions in Computational Cardiology (CFD, AI, Cardiac Imaging)

The SMART-CM project at Universidad Carlos III de Madrid (UC3M) and Hospital General Universitario Gregorio Marañón is recruiting 3 PhD students and 1 postdoctoral researcher to work on computational cardiology, focusing on stroke prevention using computational fluid dynamics (CFD), artificial intelligence (AI), and cardiac imaging. The project aims to improve personalized stratification of stroke risk in patients with atrial fibrillation by integrating non-invasive cardiac imaging, physical and computational modeling, numerical simulation, and AI to better characterize intracardiac flow, blood stasis, and thrombogenesis. Successful candidates will join a multidisciplinary team in a unique clinical-engineering environment, splitting their time between UC3M and the Department of Cardiology at Hospital Gregorio Marañón in Madrid. The research will involve advanced image-based analysis, multimodal data integration, machine learning, numerical modeling, and the deployment and maintenance of computational infrastructures supporting large-scale simulations and clinical studies. Applicants should have a background in Engineering, Physics, Applied Mathematics, Biomedical Engineering, or related fields, with strong programming skills in Python, MATLAB, or C/C++. Experience in image analysis, numerical simulation, machine learning, or scientific computing is highly valued. Knowledge of Spanish is not required, and international research stays are encouraged. The PhD positions are for up to 3 years, and the postdoctoral position is for up to 2 years, both fully funded. The start date is tentatively April 2025, with a deadline to apply by February 28, 2026. To apply, send your CV to Oscar Flores, Gonzalo R. Ríos Muñoz, or Pablo Martínez-Legazpi at the provided emails. For more information, review the project and supervisor details online. This is an excellent opportunity for motivated researchers interested in computational cardiology, stroke prevention, and interdisciplinary clinical-engineering research.