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23h59m, GMT time). Applications must be formalized by email to ritalado@fe.up.pt and to recursoshumanos@fe.up.pt , clearly stating the reference FEUP-PhD-STAR and including the following pdf documents
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://doi.org/10.54499/2023.11234.PEX , funded by national funds through FCT/MECI, under the following conditions: Scientific Area: Machine Learning applied in Applied to Fluid Dynamics Simulation Admission
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13 (5 points); Bachelor Degree classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks
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classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks, Hierarchical Decision and Control Systems with main
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a doctoral program in the scientific area of this call may apply for this grant, a requirement to be duly proven at the time of hiring. Work plan: Research activities in the field of machine learning
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within the framework of project 2023.14874.PEX - anomaly - Machine Learning-based Models for Advanced Anomaly Detection in Dam Structural Health Monitoring, with DOI https://doi.org/10.54499/2023.14874.PEX
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Intelligence Benefits and AI Learning Capabilities for Energy Consumers, with nr. 15174, operation code at the Funds Platform COMPETE2030-FEDER-00883700, funded by FEDER funds through COMPETE2030 and with
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18 Sep 2025 Job Information Organisation/Company FEUP Department Human Resources Division Research Field Engineering » Other Engineering » Biomedical engineering Engineering » Computer engineering
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within the framework of project 2023.14874.PEX - “anomaly - Machine Learning-based Models for Advanced Anomaly Detection in Dam Structural Health Monitoring”, with DOI https://doi.org/10.54499/2023.14874
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5 Sep 2025 Job Information Organisation/Company FEUP Department Human Resources Division Research Field Engineering » Computer engineering Engineering » Electrical engineering Researcher Profile