119 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" Master positions in Portugal
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of Artificial Intelligence and experience using machine learning and deep learning development environments and libraries is a plus. As set forth FCT Research Scholarship Regulation No. 950/2019 of December 16
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/InstituteFEUPCountryPortugalPostal Code8463Geofield Contact City Porto Website https://sigarra.up.pt/feup/pt Street Rua Dr. Roberto Frias Postal Code 4200-465 E-Mail recursoshumanos@fe.up.pt STATUS: EXPIRED X (formerly Twitter
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5 Jan 2026 Job Information Organisation/Company Instituto Politécnico de Bragança Department Gabinete de Apoio a Projetos Research Field Engineering » Computer engineering Researcher Profile First
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than 14/20 (1 point); B. Knowledge of Interactive Systems Design, Cyber-Physical Systems, Predictive Maintenance Systems, Automation, Machine Learning and Artificial Intelligence, Sensor Networks
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to the table of scholarships awarded directly by the FCT, I.P. in the country (https://www.fct.pt/apoios/bolsas/valores ). The period of payment of the scholarship is monthly and through bank deposit, check or
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for applications for one research grant within the framework of project ISA4RL - Integrating Instance Space Analysis with Auto-Reinforcement Learning for Adaptive Algorithm Selection and Configuration
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method applied; b) Based on the score of their academic qualifications. VII.VI- All provisional and final jury decisions must be justified, recorded in minutes, and published on https://apply.uc.pt
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of the Scientific Research Grant Holder, approved by Law No. 40/2004, of August 18, in its current wording; FCT, I.P. Research Grant Regulations, in force (https://www.fct.pt/apoios/bolsas/docs
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, in force (https://www.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019.pdf ); Regulation No. 522/2020, published in the Official Gazette, 2nd series, No. 113, of June 12 – Research Grant Regulations
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-vision algorithms with edge-computing processing for the automatic detection of non-conformities. Machine-learning techniques will be applied to optimize cutting parameters, and the module will be