Cookies Policy
We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out More
  • Menu
Research Opportunity
Apply now Final Selection Minute View Formal Call
Research Opportunity

Machine learning, computer vision


Work description

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.

Academic Qualifications

Master degree in Electrical Engineering or similar

Preference factors

Very good programming skills (C++/Python); good knowledge inf deep learning frameworks (pytorch, tensorflow). Experience in image analysis of colposcopic and cytological cervical data.

Application Period

Since 05 Feb 2019 to 18 Feb 2019


Cluster / Centre

Networked Intelligent Systems / Telecommunications and Multimedia

Scientific Advisor

Jaime Cardoso