Project inserted within the research areas of machine learning and computer vision.
[Closed]
Work description
Within the scope of the CAGED project, the detection and classification of gastrointestinal lesions is foreseen. The scholarship holder's work will take place at UTAD's facilities and are developed within the scope of this project, with the following main associated tasks: - Investigating and developing new multi-instance deep learning algorithms for detecting lesions; - Prototype development and testing
Academic Qualifications
The fellow must have a degree in Bioengineering and be a Master's student in Biomedical Engineering
Minimum profile required
Degree in Bioengineering Engineering with at least 14 values as final average mean (in 20 values).Must have computer vision knowledge, especially in deep learning methodologies in imaging.Experience in hospital imaging service.Have at least article published in an international conference.
Preference factors
Knowledge of image processing, computer vision and deep learning methods applied to medical imaging. Familiarity with applying multi-instance deep learning methods.
Application Period
Since 29 Jun 2023 to 12 Jul 2023
[Closed]
Centre
Biomedical Engineering Research