The CAGE project (INESC TEC/IPO Porto) aims to create a computer vision CAD prototype for gastric cancer screening. The fellow's work will take place at UTAD facilities and is developed within the scope of this project, with the following main tasks associated: - Investigating and developing new computer vision algorithms for lesion detection; - Developing and testing a prototype
Master's degree in Bioinformatics and PhD student in the doctoral program in computer science.
Minimum profile required
Must have at least two scientific publications, one in a journal and one in a conference, both as first author. You should have at least one year of experience as a grant recipient and participation in nationally funded projects focused on image classification and segmentation with deep learning, in particular in upper gastro-intestinal endoscopy and retinal imaging. Experience with generative convolutional networks (GANs). High expertise in automatic Glaucoma analysis using low-cost devices and deep learning methods.
Knowledge in image processing, machine learning, experience with deep-learning methods in medical imaging.
Since 18 May 2022 to 31 May 2022
Cluster / Centre
Networked Intelligent Systems / Biomedical Engineering Research