Machine learning, computer vision
The goal of the project is to improve the state-of-the-art in cervical cancer screening and diagnosis, in both cytology and colposcopy procedures, by creating a Computer Aided-Diagnosis system that can be easily integrated in the conventional clinical workflow. We seek candidates to work on machine learning/deep learning and computer vision to automatically analyze the quality of the acquired images and their suitability for diagnosis in automatic systems.
Master degree in Electrical Engineering or similar
Very good programming skills (C++/Python); good knowledge inf deep learning frameworks (pytorch, tensorflow). Experience in image analysis of colposcopic and cytological cervical data.
Since 05 Feb 2019 to 18 Feb 2019
Cluster / Centre
Networked Intelligent Systems / Telecommunications and Multimedia