The KNAW Early Career Award is intended to showcase talented PhD graduates, and to provide them with support and encouragement. The Award is aimed at researchers at the start of their career who are capable of developing innovative and original research ideas. Read more →
Computational Pathology Group
The Computational Pathology Group develops, validates and deploys novel medical image analysis methods based on deep learning technology.
Vacancies & Student projects
Development and validation of machine-learning based histopathologic skin cancer diagnostics for real-world clinical practice
Are you a creative researcher with a MSc degree in Computer/Data Science, Engineering, Technical Medicine, Biomedical Sciences or similar? Do you want to contribute to the world’s first prospectively evaluated algorithm-supported workflow for digital pathology, which will increase the time of pathologists for complex diagnostics and reduce the wait time for patients? Then we are looking for you!
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.
The goal of this project is to develop a deep learning model that can detect and classify the different types of artifacts observed in whole slide images.