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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: ● Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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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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://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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://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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benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: Research and develop novel reliable deep learning computer vision algorithms for the detection and quantification of GIM lesions
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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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algorithms; - Automation of the model customization process by conducting laboratory tests.; - Improvement of the data workflow for real-time processing and sharing.; - Data collection in experimental and real
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technological dissemination initiatives, particularly in the field of Physical or Electrical Engineering . Development of algorithms, support for the installation of the DAS, and real-time event monitoring. WORK
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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