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the average performance of algorithms is not enough to develop trust in an AI system. Reliability assessment approaches such as local fit and density principles try to address the problem of uncertainty in deep
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. OBJECTIVES: The interest in direct current (DC) power distribution systems has been growing significantly, driven by the increasing use of power electronics-based loads and the rise of distributed energy
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on artificial intelligence (AI) for energy systems and electrical grids - Execution of functional tests to validate the safety and robustness features of AI, taking into account the data-driven nature of AI and
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: Scientific Advisor: César Toscano Duration of the contract: from 2025-11-19 to eventually renewable. Location: INESC TEC, Porto, Portugal Job description: Work Area: Computer Engineering Project overview
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-time monitoring.; • Develop numerical models to simulate the dynamic behavior of mooring and anchoring systems under different environmental conditions.; • Analyze and optimize structural performance and
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industry needs. One of the laboratories involved is the x-Energy Lab – SmartGrids and Electric Vehicles Laboratory, part of INESC TEC’s Centre for Power and Energy Systems.; It is in this context that INESC
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the application of the selected methods ; - Apply the scientific method on the research process and a critical attitude on the obtained results.; 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING
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industry needs. One of the laboratories involved is the x-Energy Lab – SmartGrids and Electric Vehicles Laboratory, part of INESC TEC’s Centre for Power and Energy Systems.; It is in this context that INESC
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on artificial intelligence (AI) for energy systems and electrical grids ; - Execution of functional tests to validate the safety and robustness features of AI, taking into account the data-driven nature of AI and
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the profile of the selected candidate. Job Summary: INESC TEC is inviting for applications for a researcher to join the Center for Innovation, Technology and Entrepreneurship and work in the field