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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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) videos. 3. BRIEF PRESENTATION OF THE WORK PROGRAMME AND TRAINING: The fellow will contribute to developing artificial intelligence-based solutions for the automated analysis of polysomnography (vPSG
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.; - Develop skills in artificial intelligence and machine learning techniques for analyzing operational data and detecting anomalies, using foundational model approaches (e.g., GridFM project, LF Energy
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - knowledge of wireless networks; - knowledge of Artificial Intelligence models.; Minimum
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of Tuition fees to grant holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Artificial intelligence
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programme of R&D projects geared towards the development and implementation of advanced cybersecurity, artificial intelligence and data science systems in public administration, as well as a scientific
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of a multi-modal dataset.; - Implementation of a software module for storing datasets according to a pre-defined standard.; - Development of routines for testing existing ML algorithms on a multimodal
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acceptance by technology takers and final users.; ; The main objectives of the Fellowship are:; 1) Apply data analysis and identify energy management use cases in renewable energy communities and industry.; 2
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intelligent surfaces ; - Identification and selection of the most adequate optimization methods to address the proposed workplan: ; - Develop the research skills through the application of the selected methods
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experience in programming with R and RStudio.; Knowledge of Data Visualisation and Multivariate Analysis.; Minimum requirements: Enrolled in a Master’s program in the relevant admission area. Knowledge