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protocols for data collection with motion capture systems and curation of the resulting data - Design generative models for the creation of human movement datasets for training AI models - Evaluate
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, floater, moorings, and cables) and combines them with an advanced robotic hub for inspection and data collection in the marine environment.; •Developing data analysis methodologies and numerical modelling
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/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: The overall vision of the ATE is to deploy and demonstrate a set of business models
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architectures for the energy and power management system on ships Develop control and dispatch strategies for hybrid microgrids, taking into account the specific power and energy requirements of ships Modeling
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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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Institutions. Preference factors: • Experience with computational simulation models / MATLAB/Simulink.; • Knowledge of industrial-grade communication protocols (Modbus TCP, IEC 61850, etc.). ; Minimum
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AND TRAINING: - Development of model/process chains that enable AI-based assistants to support human operators' decisions in power systems under model risk and uncertainty, and considering joint human
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study cycle or non-award courses of Higher Education Institutions. Preference factors: • Experience with computational simulation models / MATLAB/Simulink.; • Knowledge of industrial-grade communication
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AND TRAINING: - Development of model/process chains that enable AI-based assistants to support human operators' decisions in power systems under model risk and uncertainty, and considering joint human
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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