Peritubular Capillary Segmentation in Kidney Transplant Biopsies
Automatically segmentation of peritubular capillaries
We always welcome applications from strong candidates. Feel free to send your CV to a staff member if you are interested to join DIAG. If you consider applying please read this general information about doing a PhD at DIAG.
There are no vacancies at the moment.
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.
Automatically segmentation of peritubular capillaries
Extending kidney tissue segmentation algorithm to other tissue compartements
Development of a deep learning algorithm for automated diagnosis of DRESS syndrome
Use quantified pathomics features to help improve survival prediction for PDAC patients
Development of deep learning methods to characterize PD-L1 positive cells in lung cancer immunohistochemistry for automatic biomarker extraction
Development of a deep learning algorithm for automated whole-slide pathology image analysis and quality control
Development of deep learning methods to combine Tumor-Infiltrating Lymphocytes (TILs) and Tertiary Lymphoid Structures (TLS) in Non-Small Cell Lung Cancer histopathology images
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