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Support Technician Position
hace 3 semanas
**Job Reference**: 20241220_ALETHEIA
About CVC
The Computer Vision Center (CVC) is a non-profit research center established in 1995 by the Generalitat de Catalunya and the Universitat Autònoma de Barcelona (UAB). Its mission is to carry out cutting-edge research that has the highest international impact in the field of computer vision. It also promotes the transference of knowledge to industry and society.
Computer vision is an exciting research area and an omnipresent technology, essentially empowering machines with the sense of vision. The CVC is a successful marriage between knowledge and innovation. In addition to our cutting-edge scientific achievements, we have established lasting ties with industrial partners and created several spin-off companies.
**Research area or group**: Image Sequence Evaluation
Context and Mission
**This position is linked to Zero Forgetting In Neural Networks**: Continual Learning With Anomaly Detection In Image Sequences (Aletheia), funded by Spanish Government (Ministerio de Ciencia, Innovación y Universades & AEI).
Main responsibilities
Development and validation of techniques for detecting lesions in colonoscopy images and videos.
Integration of spatiotemporal tracking tools for lesions to improve the performance of lesion detection systems in colonoscopy images and videos.
Development and validation of techniques for classifying polyps in static images and colonoscopy videos.
**Requirements**:
Bachelor’s Degree in Computations Mathematics and Data Analytics
Fluency in English
Prior experience in Deep Learning techniques will be highly avaluated.
Conditions
The position will be located at Computer Vision Center (Campus Universitat Autònoma de Barcelona).
We offer a half-time contract (20 h/week) temporary contract, a good environment, flexible working hours
**Starting date**: 17th January 2025
Applications procedure and process
**Deadline**: 03/01/2025
This contract is part of the R & D project PID2020-120611RB-I00, funded by MICIU/AEI/10.13039/501100011033.
OTM-R principles for selection processes
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