PhD candidate 'Automated analysis of coronary OCT images'

Note: This application has been filled. Please see our Vacancies page for open vacancies.

PhD candidate 'Automated analysis of coronary OCT images'

Job description

We are seeking a highly motivated and talented individual to join our new team as a PhD-candidate at the CARA Lab, a multi-disciplinary and multi-institutional collaboration between Radboudumc and Amsterdam UMC.

This lab is part of the 10-year LTP ROBUST program “Trustworthy AI-based Systems for Sustainable Growth” consortium, which unites 17 knowledge institutions, 19 participating industry sponsors and 15 civil-social organisations from across the Netherlands. You will gain valuable experience working with an industry partner, and will be able to tap into a wealth of networking, career development, and training opportunities in conjunction with ICAI, the Innovation Center for Artificial Intelligence at the University of Amsterdam.

The CARA Lab is a dynamic and innovative research group focused on the integration of advanced medical imaging and artificial intelligence technologies to improve diagnosis and treatment of cardiovascular diseases, especially coronary artery disease. The lab is a collaboration between Radboudumc, Amsterdam UMC and Abbott, a world-leading international medical device company.

As our PhD-candidate you will be involved in the development of AI algorithms for segmentation and real-time analysis of optical coherence tomography (OCT) images of the coronary arteries, obtained during cardiac catheterization procedures. The role will be based at the Radboudumc, with occasional visits to Amsterdam. The project will require a combination of technical and scientific skills, including expertise in image analysis, machine learning, and software development. You will work closely with a multidisciplinary team of cardiologists, engineers, and industrial partners, and will have the opportunity to contribute to the development of cutting-edge technology that has the potential to transform the field of cardiovascular imaging.

Tasks and responsibilites

  • Conduct research in the development of AI algorithms for segmentation and real-time analysis of OCT images.
  • Collaborate with a multidisciplinary team to translate cutting-edge technology into clinical practice.
  • Publish research findings in peer-reviewed journals and present at international conferences.
  • Mentor junior team members and contribute to the development of the lab's research direction.


Are you a talented researcher with a passion for innovation in the fields of computer science, physics, engineering, or biomedical sciences? Do you have a strong interest in the development of cutting-edge artificial intelligence algorithms that can be applied to improve healthcare and cardiology? Are you a skilled communicator with a knack for working effectively in diverse, interdisciplinary teams? If you also possess expertise in software development, particularly in Python, and have experience in areas such as deep learning, machine learning, and image or time series analysis, we want to hear from you.

Join us as we explore the frontiers of AI research and apply these advancements to the vital field of healthcare. Apply now to be part of a dynamic team of innovators!


Please apply here. You should supply a motivation letter, your CV, links to a Google Scholar profile, a list of grades and courses you have followed including online courses on deep learning and similar topics, and links to any publications you have written plus any code you have written and is publicly accessible, e.g., on a GitHub account. Applications are processed immediately upon receipt.


Ivana Isgum

Ivana Isgum

Jos Thannhauser

Jos Thannhauser

Assistant Professor, Lab Contact

Diagnostic Image Analysis Group