Vacancy: Deep learning for oncologic imaging

The Diagnostic Image Analysis Group (DIAG) of the Radboud University Medical Center, Nijmegen, is offering a PhD position.



Patients with cancer typically undergo many imaging exams. First, imaging is used for diagnosis and staging. During and after treatment, imaging is used to monitor the progression of the disease. Radiologists need to carefully go over these scans, and compare them with the prior scans of the same patient. These scans can contain up to 1000 slices which need to be inspected. Radiologists search for new lesions, measure old lesions to see if they grow or shrink, and look for other signs of disease development. This is a very complex and time-consuming task.

The Diagnostic Image Analysis Group and Fraunhofer MEVIS have started a large joint project called Automation in Medical Imaging (AMI). Funded by Radboud University and Radboud University Medical Center and the Fraunhofer Gesellschaft as an ICON project, AMI will develop a generic platform for automatic medical image analysis. One of the applications within the AMI project is the developing of an oncology solution. In this part of AMI, we are developing an optimized software environment that assists radiologists in reading oncological scans more accurately and more quickly. You will work in this part of AMI. We are using deep learning to locate and segment organs, to find lesions in organs, to automatically assess change between scans, etc. You will implement the developed software into CIRRUS, our development environment built on top of MeVisLab, in order to provide a complete product ready to be deployed in clinical practice.


You should be a creative and enthusiastic researcher with an MSc degree in Computer Science, Physics, Engineering or Biomedical Sciences or similar, with a clear interest to develop image analysis algorithms and an affinity with medical topics. Experience with machine learning, deep learning, and image analysis is a pre. Good communication skills and expertise in software development, preferably in C++ and Python, are essential.

Terms of employment

You will be appointed as a PhD student with the standard salary and secondary conditions for PhD students in the Netherlands. Your performance will be evaluated after 1 year. If the evaluation is positive, the contract will be extended by 3 years. The research should result in a PhD thesis.


The Diagnostic Image Analysis Group (DIAG) is a research division of the Department of Radiology and Nuclear Medicine of the Radboud University Medical Center in Nijmegen. Nijmegen is the oldest Dutch city with a rich history and one of the liveliest city centers in the Netherlands. Radboud University has over 17,000 students. Radboud UMC is a leading academic center for medical science, education and health care with over 8,500 staff and 3,000 students.

The focus of the Diagnostic Image Analysis group is the development and validation of novel methods in a broad range of medical imaging applications. Research topics include image analysis, image segmentation, machine learning, and the design of decision support systems. Application areas include breast imaging, prostate imaging, digital pathology, lung imaging, and retinal imaging. Key to the success of the group is close cooperation with clinicians. Currently the group consists of around 40 researchers.


For more information please contact Colin Jacobs by e-mail.


Please apply by following this link. Only if this does not work, you can send applications as a single pdf file to and In this pdf file the following should be included: CV, list of followed courses and grades, letter of motivation, and preferably a reprint of your Master thesis or any publications in English you have written. This application will remain open until the position has been filled. Applications are processed immediately upon receipt.