In this project you will develop new machine learning methods for end-to-end training on gigapixel-sized images, investigate AI explainability and transfer learning strategies, and work with algorithms for content-based image retrieval and federated learning. You will work together with the over forty partners in the consortium which spans almost the entirety of Europe (and even further), including both academic partners, small, and big corporations.
The starting date for this position is 1 February 2022. Working at Radboud university medical center means that you are ahead of the curve and working together on the healthcare of the future. And there is more. Our secondary terms of employment are impressive. These are fully tailored to you thanks to our Employment Conditions Selection Model. At Radboud university medical center, you will be given trust, and you will take the responsibility to handle everything together. We provide annual courses, both professional and personal.
- In addition to your monthly salary and an annual vacation allowance of 8%, you will receive an end-of-year bonus of 8.3%.
- If you work irregular hours, you will receive an allowance.
- As a full-time employee (36 hours per week), you are entitled to approximately 168 vacation hours (over 23 days) per year.
- Radboud university medical center pays 70% of the pension premium. You pay the rest of the premium with your gross salary.
- You get a discount on health insurance as well: you can take advantage of two group health insurance plans. UMC Zorgverzekering and CZ collectief.
In addition to our terms of employment, we also offer employees various other attractive facilities, such as childcare and sports facilities. Want to learn more? Take a look at the Cao UMC. 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 the departments of Radiology and Nuclear Medicine, Pathology and Ophthalmology.
We develop, validate and deploy novel medical image analysis methods, usually based on deep learning technology and focusing on computer-aided diagnosis (CAD). 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 and Panda grand challenges which we organized.
At the moment there are more than 1,300 PhD candidates at our medical hospital. This number includes PhD candidates on our pay roll as well as external candidates (those employed somewhere else but researching on our premises).
- Radboud Institute for Health Sciences: ± 700
- Radboud Institute for Molecular Life Sciences: ± 400
- Donders Center for Medical Neurosciences: ± 200
Read what it is like to do a PhD at the Radboud University Medical Center.
Radboud university medical center is a university medical center for patient care, scientific research, and education in Nijmegen. Radboud university medical center strives to be at the forefront of shaping the healthcare of the future. We do this in a person-centered and innovative way, and in close collaboration with our network. We want to have a significant impact on healthcare. We want to improve with each passing day, continuously working towards better healthcare, research, and education. And gaining a better understanding of how diseases arise and how we can prevent, treat, and cure them, day in and day out. This way, every patient always receives the best healthcare, now and in the future. Because that is why we do what we do.
Read more about our strategy and what working at Radboud university medical center means. Our colleagues would be happy to tell you about it. #weareradboudumc We are looking for a creative and ambitious PhD candidate with good communication and organizational skills. It is important that you have a clear interest in artificial intelligence and medical image analysis.
- MSc degree in Computer Science, Data Science, Engineering, Technical Medicine, Biomedical Sciences or similar.
- Experience with deep learning and programming, preferably in Python, are a plus and should be evident from the (online) courses you’ve followed, your publications, GitHub account, etc.
All additional information about the vacancy can be obtained from dr.ir. Geert Litjens, assistant professor Pathology. Use the Apply button to submit your application.