22 machine-learning "https:" "https:" "UCL" positions at Instituto de Telecomunicações
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techniques and machine learning algorithms. The goal is to decipher patterns in the bioelectrical signals. Project UID-50008-2025 funded by FCT-Fundação para a Ciência e a Tecnologia. Scientific Area: Basic
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NEXUS – Nexus of Multidisciplinary Approaches in Explainable and Causal Machine Learning. This project is funded by national funds through FCT – Fundação para a Ciência e a Tecnologia, I.P., and, when
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Area: Computer Vision Group: Pattern and Image Analysis Work Objectives: In terms of deep learning architectures for object detection, particular attention will be given to the analysis of performance
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on artificial intelligence techniques, namely machine learning and deep learning; (3) analysing mathematical models applicable to renewable energy generation technologies and electrical energy storage systems; (4
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of the mobility platform with computer vision and AI. Applicable Legislation: Labour Code, approved by Law no. 7/2009, of 12 February, in its current reading. The selection panel shall be Prof. Dr. Susana Sargento
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of an academic degree or in a non-degree course, must be submitted by the time of contract signing. Apply online clicking on the “Apply Now” button in this form https://www.it.pt/Positions/OtherResearchPosition
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compression, event-based or neuromorphic vision, signal processing, machine learning or deep learning for visual data. - Motivation for research and scientific dissemination. - Good communication skills in
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12 Feb 2026 Job Information Organisation/Company Instituto de Telecomunicações Research Field Engineering » Electrical engineering Engineering » Computer engineering Computer science » Computer
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27 Feb 2026 Job Information Organisation/Company Instituto de Telecomunicações Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Bachelor
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and signature matching based on existing code. - Performance evaluation of the application on a Raspberry Pi (RPi). - Development of improvements to machine learning algorithms for anomaly detection and