Vacancy Postdoctoral researchers in two projects on computational pathology

Job description

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.

Place of work

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.

Profile

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.

Employment conditions

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. 

And there is more..

• An Employment Conditions Selection Model, allowing you to use part of your employment conditions to your choosing. For example, you can use your gross salary to purchase additional vacation hours or hours for providing informal caregiving. Or, for example, you can use your gross end-of-year bonus to purchase a bicycle, so you pay less tax.
• Plenty of opportunities for personal development. You can take a variety of courses in our online learning environment. 
• Your well-being and vitality are a priority. For example:
  • Save time for work-life balance leave. 
  • You can enjoy unlimited access to a variety of activities five days a month and take advantage of all the facilities at Radboud Sport & Culture for only €27.05 per month (instead of €41)
  • Healthy Professionals program to help you manage your energy. 
  • Company Support Team and a personal coach if you are going through a life-changing event.
  • Financially beneficial working less through a Generation Scheme as you approach state pension age.
• Support in achieving a good work-life balance at every stage of your life. Examples:
  • Advice and courses on, for example, 'Millennial dilemmas' and 'Your Career After 57'.
  • Activities at our own mindfulness center.
  • Informal caregiving consultations if you have questions about juggling work and caregiving responsibilities at home.
• In addition to statutory pregnancy and maternity leave, Radboud university medical center offers 26 weeks of parental leave, nine of which are paid. In addition, as a partner you can take a maximum of five weeks of supplementary partner leave. During supplementary partner leave and parental leave, we supplement the UWV benefit up to 100% of your salary.
• Pension accrual at the ABP Pension Fund. Radboud university medical center pays 70% of the pension premium. 
• Discounts on supplementary packages of two group health insurances and ten other types of insurance, from home insurance to legal assistance.
• An allowance for your commuting costs of € 0.18 per km up to a maximum of 40 km one way. If you use public transport to commute, we will fully reimburse the public transport costs (2nd class). If you regularly work from home, you will receive a working from home allowance of € 2.40 per day.

 

Application procedure

Are you ready to think further for our patients and our care? We would like to receive your application before 5 June 2025. We will then contact you shortly. The job interviews takes place in week 24 (9-13 June 2025). We would appreciate it if you would take this into account. If you have a preference for a specific project, please mention this in your application letter.

Good to know

• This position requires a Certificate of Conduct (VOG).
• You can find more information about our application procedure and frequently asked questions on our website.
• Will you be our new colleague? Then you will be given the time and space to get to know your role, your workplace, and your colleagues. An induction day for all new colleagues is an integral part of your onboarding program. 

We are recruiting for this position ourselves. Unsolicited marketing is not appreciated, but do feel free to share the vacancy in your network!

Contact

Any questions? Or wondering what it is like to work at Radboudumc? Then call, send a message or email to Francesco Ciompi, associate professor via +316 53 34 11 47. Use the Apply button to submit your application.