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algorithms; Minimum requirements: - experience with cross-platform mobile development frameworks (Ionic); - experience in software development using the Python programming language. 5. EVALUATION
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initiatives, particularly in the field of Energy Systems - Energy Transition. The objectives are:; - Development and application of artificial intelligence algorithms for different use cases in the energy
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-oriented interfaces is desired.; In parallel, we intend to explore new optimizations, such as data deduplication, support for multi tenancy, and new scheduling algorithms. These optimizations should be
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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to explore new optimizations, such as data deduplication, support for multi tenancy, and new scheduling algorithms. These optimizations should be implemented and integrated into the platform.; Implementation
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selection of sensors and their respective lighting to be adopted.; 3. Study and development of algorithms for detecting inconsistencies.; 4. Study and implementation of operator interfaces.; 5. Assembly and
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://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - Development and testing of algorithms and methodologies based
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. Implementation of signal detection algorithms and triangulation ; 4. Planning and participating in field tests to evaluate system performance; 5. Reporting and disseminating the work developed (ideally with a
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suitable voltage and frequency control strategies, based on state-of-the-art research, and development of dispatch algorithms for the isolated microgrid, considering the coordinated control of generation
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OF THE WORK PROGRAMME AND TRAINING: 1) Development of workflows and algorithms to complement datasets of connected data spaces, to improve analysis results (forecasting, analysis of financial tools, predictive