PhD AI-based cardiovascular image analysis and modeling

SIGRA; Amsterdam; On-site; EUR 36,000 - 45,000; Full time

Benefits offered by this job

BeFrank pension

Public transport reimbursement

Bike scheme

8.3% end-of-year bonus

Job summary

SIGRA, in partnership with Amsterdam UMC Research BV, offers a PhD-position focused on AI-enabled cardiovascular imaging and probabilistic digital twins of coronary arteries. The project combines medical imaging, generative AI, and hemodynamics to support decision-making during catheterization.

As a PhD candidate, you will work with large clinical datasets, validate methods across centers, and contribute to high-impact publications. English proficiency is required for communication and writing.

Qualifications

• MSc in biomedical engineering, applied mathematics, computer science, physics or related field.
• Experience with Python and PyTorch for scientific computing.
• Affinity with medical image analysis and computational modeling.
• Familiarity with neural networks for image analysis or physics-informed ML.
• Excellent English communication and collaboration with clinicians.

Responsibilities

• Develop deep generative models for uncertainty-aware 3D reconstruction of coronary anatomy.
• Create physics-informed neural networks for fast 3D hemodynamics estimation.
• Design pipelines integrating image-based anatomy, blood flow physics, and uncertainty quantification.
• Validate methods on retrospective multi-center datasets with clinical partners.
• Disseminate results via scientific articles and presentations.

Skills

Scientific programming

Python

PyTorch

Medical image analysis

Computational modeling

Neural networks for image analysis

Interdisciplinary collaboration

English communication

Education

MSc in biomedical engineering, applied mathematics, computer science, physics or related

Tools

Python

PyTorch

Job description

Do you want to develop deep learning methods to create digital twins of coronary arteries? And help interventional cardiologists make smarter, data-driven treatment decisions in real time?

You will contribute to a translational research project aimed at improving the diagnosis and treatment of coronary artery disease and supporting clinical decision-making during catheterization procedures. The project brings together cardiovascular imaging, generative AI, and computational modeling to develop probabilistic digital twins of coronary arteries.

The goal is to create patient-specific models that combine anatomical and hemodynamic information derived from routine clinical imaging. By providing quantitative insights into coronary anatomy, blood flow, pressure, and wall shear stress—together with information about model uncertainty—the project aims to support more precise, physiology-guided treatment decisions without the need for additional invasive measurements.

The research is embedded within the Quantitative Healthcare Analysis (qurAI) group and conducted in close collaboration with the CARA Lab and clinical partners in the Netherlands and abroad. You will work with large, multi-center clinical datasets and contribute to translating advanced computational methods into clinically relevant applications.

This PhD position offers a unique opportunity to work at the intersection of artificial intelligence, cardiovascular engineering, and clinical medicine, with the potential to contribute directly to the future of personalized cardiovascular care.

As a PhD candidate, you will work on improving the diagnosis and treatment of coronary artery disease, with a clear focus on clinical application during catheterization procedures. Your research sits at the intersection of medical image analysis, generative AI, and blood flow modeling.

You will

• develop deep generative models (such as latent diffusion models, implicit neural representations, and flow matching) for uncertainty-aware 3D reconstruction of coronary anatomy from 2D X-ray angiography;
• develop physics-informed neural networks and graph-based neural operators for fast estimation of 3D coronary hemodynamics (velocity, pressure, and wall shear stress fields);
• design computational pipelines that integrate image-based anatomy, blood flow physics, and uncertainty quantification;
• validate the developed methods on retrospective multi-center clinical datasets, in collaboration with clinical partners in the Netherlands and abroad;
• critically assess model performance and interpret results in the context of clinical and hemodynamic relevance;
• write scientific articles for high-impact journals and present your findings at national and international conferences and workshops.

You are a motivated researcher with a strong technical background and a genuine interest in applying artificial intelligence to real clinical problems. You are curious, creative, and rigorous: you enjoy developing new methods and you care deeply about thorough validation and their impact on patient care.

You have

• an MSc degree in biomedical engineering, applied mathematics, computer science, physics or a related discipline;
• demonstrable experience with scientific programming (preferably in Python, including deep learning frameworks such as PyTorch);
• affinity with medical image analysis and computational modeling;
• experience with neural networks for image analysis, generative modeling, geometric deep learning or physics-informed machine learning, or you are willing to learn these quickly;
• strong collaboration skills: you enjoy working in a multidisciplinary team and feel comfortable interacting with clinicians;
• excellent English communication skills (speaking and writing); only applications in English will be considered.

Experience with cardiovascular imaging or computational fluid dynamics is an advantage.

• A flying start to your career in scientific research, with the opportunity to obtain a PhD degree.
• Plenty of room for your drive to shape tomorrow's healthcare.
• Working on large-scale and in-house research, with motivated colleagues from all over the world.
• You will be employed by Amsterdam UMC Research BV.
• A contract for 4 years (initial contract of 1 year, extended upon good performance).
• Classification in salary scale OIO: € 3.217 to € 4.077 gross for full-time employment (depending on experience). In addition to a good basic salary, we offer 8.3% end-of-year bonus. Calculate your net salary here.
• Holiday hours: 190.4 per year for fulltime and a possibility to save additional hours.
• Pension accrual with BeFrank, a modern, comprehensible and fairly priced pension.
• For >7 km each way, 100% reimbursement for public transport travel costs and, for private transport, €0.18 per km up to a maximum of 40 km each way.
• Do you prefer walking or cycling? Take advantage of our good bike scheme. Moreover, you will receive a reimbursement of €0.18 per km.

You will join the department of Biomedical Engineering & Physics at Amsterdam UMC. This department is one of the technical engines behind clinical and research innovation and participates in numerous international projects and studies.

The PhD project is embedded within the qurAI group, where researchers work on quantitative healthcare analysis. The team has extensive experience in developing and validating AI-based image analysis methods and a strong track record in cardiovascular imaging research. You will be part of an active group of PhD candidates and postdocs developing AI methods for quantitative analysis of medical images and signals.

You will also collaborate closely with researchers and cardiologists in the CARA lab. In this multidisciplinary environment, joint method development, data analysis and clinical implementation go hand in hand. In this way, you contribute directly to innovative, safer and more accessible cardiovascular care.

Amsterdam UMC Research BV

Amsterdam UMC Research BV supports non-profit scientific research. In doing so, we provide researchers with everything they need to excel. Our principal investigators (PIs) and project leaders offer support in the field of project management, finance and human resources. In medical scientific research projects, legal support is also provided.

Watch the video to find out more.

During the publication period, applications will be handled continuously. If the vacancy is filled, it will be closed prematurely.

If you have any questions about this position, please feel free to contact Simone Saitta, via [e-mail].

A reference check, screening and hiring test may be part of the procedure. Read here whether that applies to you. If you join us, we ask you for a VOG (Certificate of Good Conduct).

Internal candidates will be given priority over external candidates in case of equal suitability.

Acquisition in response to this vacancy is not appreciated.