Postdoctoral Positions in Machine Learning and MRI Physics for Cardiovascular Imaging at Karolinska Institutet

Karolinska Institutet is seeking up to two fully funded postdoctoral researchers to join the ERC-funded MultiPRESS project, focusing on advancing phase-contrast MRI for cardiovascular diagnostics. The positions are based in the Department of Molecular Medicine and Surgery (MMK) and supervised by Assistant Professor David Marlevi. The research environment is highly translational, integrating clinical science, biomedical engineering, and medical physics to improve cardiovascular disease diagnostics. Position 1: Postdoc in Machine Learning for Cardiovascular Imaging This role involves developing and applying machine learning techniques, particularly neural networks, for improved hemodynamic risk prediction using cardiovascular imaging, with a focus on four-dimensional flow magnetic resonance imaging (4D Flow MRI). The work includes enhancing data-driven imaging networks, processing algorithms, and expanding into advanced network architectures such as Diffusion, Transformer, or Foundation Model networks. The successful candidate will work with patient-specific models, benchtop validation, and clinical patient cohorts, aiming to streamline analysis and improve physiological insight in cardiovascular diagnostics. Position 2: Postdoc in MR Physics This position centers on sequence development, image reconstruction, and data-driven image analysis for next-generation MRI. The focus is on developing novel pulse sequences and image reconstructions for 4D flow imaging, addressing challenges such as scan time, motion artifacts, and spatiotemporal resolution. The candidate will evaluate methods using on-site MRI scanners and clinical cohorts, contributing to the translation of imaging innovations into clinical practice. Eligibility and Requirements: Applicants must hold a PhD or equivalent, ideally completed within the last three years. For the machine learning position, expertise in scientific machine learning, neural network programming (TensorFlow or PyTorch), and high-performance computing is essential. For the MR physics position, a PhD in MR physics, experience in MRI physics, and programming skills (C++, Python) are required; Siemens IDEA environment experience is advantageous. Excellent English communication skills and the ability to work in a multidisciplinary, international team are required. Experience in medical imaging, clinical studies, or cardiovascular MR imaging is desirable but not mandatory. Funding and Benefits: Both positions are fully funded as part of the ERC-funded MultiPRESS project and a European research initiative. The roles offer access to state-of-the-art imaging equipment, computational resources, and university benefits. The research group is deeply integrated with clinical activities at Karolinska University Hospital, providing opportunities for groundbreaking research and career development. Application Process: Applications must be submitted through the Varbi recruitment system by March 16, 2026. Required documents include a PhD certificate, complete CV, publication list, and a summary of current work. All documents should be in English or Swedish. For more information, contact Assistant Professor David Marlevi at [email protected]. Keywords: cardiovascular imaging, machine learning, magnetic resonance imaging, MR physics, 4D Flow MRI, data-driven imaging, neural networks, image reconstruction, medical imaging, hemodynamics.