Postdoctoral researchers in two projects on computational pathology

Our Computational Pathology Group at Radboud University Medical Center in Nijmegen (Netherlands) is looking for postdoctoral researchers in two projects on computational pathology. The arsenal of medical treatments such as immune and targeted therapies is rapidly expanding, but most drugs only benefit a fraction of patients. One of the goals of our research is the development and validation of artificial intelligence techniques which serve as prognostic or predictive biomarkers to identify which particular patient or tumor type will respond to a specific treatment. Are you one of our new postdocs?

Project 1 (NWO-funded) we investigate “Dynamic 3D Biopsy Based Response to Treatment Prediction” (DoPredict), by analyzing the effect of multiple applied drugs on cultured biopsies of an individual patient. Cultured cells of acute biopsies of lung cancer are imaged with label-free higher harmonic generation (HHG) microscopy, monitoring the tissue in 3D during culturing. This innovative approach will generate data describing the temporal dynamics of cells in the tumor-immune microenvironment in 3D, possibly identifying the optimal treatment for individual patients within 5-7 days.

Tasks and responsibilities

• Work in close collaboration with PhD candidates working at Radboudumc, the VU and AmsterdamUMC to develop artificial intelligence for advanced analysis of HHG images and use it to characterize the tumor-immune microenvironment (TIME) in lung tissue.
• Develop AI to automatically detect, segment, classify and track cells in HHG 3D+T images, also using recent approaches based on foundation models.
• Develop temporal cell tracking algorithms to automatically determine the 3D trajectory of cells over time.
• Develop methods to assess treatment response by turning morphological and temporal information into quantifiable biomarkers that can be correlated with response to treatment, also using approached based on graphical models.

Project 2 (KWF-funded) we investigate the use of AI to identify sub-groups of breast cancer patients that are candidates for therapy escalation or de-escalation. The project focuses on commonly available pathology slides, in order to yield solutions that can readily be implemented in routine clinical practice. The project is mostly translational, focusing on providing evidence on biomarkers as well as on implementation.

Tasks and responsibilities

• Work in close collaboration with the breast cancer research group working at Radboudumc, to develop artificial intelligence for analysis of breast cancer tissue sections.
• (Co-)supervise PhD students on the project.

As a postdoc you should be a creative and enthusiastic researcher with a PhD degree in a relevant field, such as medical image analysis, computer vision, or machine learning. You should have a clear interest to develop image analysis algorithms and an affinity with oncology or medical topics. Good communication skills and expertise in software development, preferably in Python, are essential. Previous experience with (co-)supervision of junior researchers such as PhD students, as well as experience with graph neural networks and foundation models is a plus.

At Radboud university medical center, you build on your future. We are committed to providing the best care, education, and research. And we are true to our word, because we help you develop and seize opportunities and give you the room to grow. As an employer, we believe that employees should feel vital and happy at work in all stages of life. We are also committed to creating a healthy and safe working environment. Our employment conditions contribute to that. What we offer:

• A gross monthly salary between € 3.493 and € 5.504 (scale 10) for full-time employment (36 hours per week). You will also receive an 8% holiday allowance, an 8.3% end-of-year bonus, and, depending on the position, an allowance of 47% to 72% for working irregular hours.
• From 1 July 2025 an increase in salary with 3%.
• 176 vacation hours per year based on a 36-hour working week.

The Computational Pathology Group is a research group of the department of Pathology of the Radboud University Medical Center (Radboudumc). We are also part of the cross-departmental Diagnostic Image Analysis Group (DIAG) at Radboudumc, with researchers in other departments, such as Radiology and Nuclear Medicine, Cardiology, Radiotherapy and Pathology.

We develop, validate and deploy novel medical image analysis methods, usually based on the newest advances in artificial intelligence with a focus on computer-aided diagnosis (CAD) as well as predictive and prognostic biomarkers in oncology. Application areas include diagnostics and prognostics of breast, colon, prostate and lung cancer. Our group is among the international front runners in the field, witnessed for instance by the highly successful Camelyon, Panda and Tiger grand challenges which we organized.

You will work in close collaboration with (inter)national project partners. Specifically for the first position, this is a close collaboration with the Vrije Universiteit (VU), the Amsterdam University Medical Center (AmsterdamUMC) and the company FlashPathology BV, spin-off of the VU that has built the label-free microscopy device based on higher harmonic generation technology (with one prototype available at Radboudumc). In the second project we collaborate with Dutch Cancer Institute (NKI) Amsterdam, our spinoff Aiosyn as well as a range of international academic partners (Europe and US).

Radboudumc
Welcome to Radboud university medical center (Radboudumc), where our research groups strive for innovative solutions that make impact on health and healthcare. We challenge the status quo to overcome current and future health challenges. Our goal is to shape the future of healthcare for generations to come. Our focus is on prevention, sustainability, and meaningful care, which we achieve through our in-depth understanding of disease mechanisms, clinical science, public health research, medical technology and data science. Our approach is centered on breakthroughs that can truly enhance personalized healthcare and public health.

At Radboudumc, a comprehensive range of research programs provide the compass for our research efforts. Each program has a clear goal, where collaboration within and outside our organization is highly valued. We integrate care, education and research in partnership with our patients to ensure that our research programs have significant impact on health and healthcare. We invite you to join us in our mission to create a healthy future for all.