PhD Candidate for AI-based prostate cancer assessment at CWZ and Radboudumc
PhD Candidate for "Improving assessment of adverse histopathology on multi-parametric prostate MRI using AI and radiology-pathology fusion" at CWZ and Radboudumc
PhD Candidate for "Improving assessment of adverse histopathology on multi-parametric prostate MRI using AI and radiology-pathology fusion" at CWZ and Radboudumc
We welcome good master's and bachelor's students to perform academic research in our group. We offer various projects that can be tuned to match your thesis requirements. You can also browse through our research pages to read about the different research topics of our group.
Aim of the presently proposed ‘proof of concept‘ study is to develop digital pattern recognition algorithms (more specifically: deep neural networks) for the extraction of morphological features from scanned H&E stained tissue sections from TNBC which are indicative for the risk of recurrence.
Automatically segmentation of peritubular capillaries
Extending kidney tissue segmentation algorithm to other tissue compartements
Development of deep learning methods for multimodal registration in prostate cancer
Development of a deep learning algorithm for automated diagnosis of DRESS syndrome
Use quantified pathomics features to help improve survival prediction for PDAC patients
The positions below are closed, please do not apply. They are listed to give you an idea of the kind of positions we regularly offer.
Vacancies