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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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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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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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in hypervision, decision support systems, and AI agents applied to power grid operations (based on LF Energy's GridFM and OperatorFabric projects).; - Scenario modeling using real and synthetic data
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-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: In this project, we intend to develop a new approach based on physically inspired hybrid machine
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generative models for the creation of human movement datasets for training AI models; - Prepare activity reports and scientific articles. 4. REQUIRED PROFILE: Admission requirements: - Master's student, with a
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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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/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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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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study cycle or non-award courses of Higher Education Institutions. Preference factors: • Experience with computational simulation models / MATLAB/Simulink.; • Knowledge of industrial-grade communication