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HIL environment rather than only on offline simulation. Learning outcomes anticipated include stronger understanding through immediate feedback on live systems, deeper engagement with
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, Automation, Machine Learning and Artificial Intelligence, Sensor Networks, Hierarchical Decision and Control Systems, with a primary focus on manufacturing and autonomous systems. (1 to 5 points); C
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electrical and Computers Engineering - Specialization in Automation - lower than 13/20 (1 point); B. Knowledge of Cyber-Physical Systems, Predictive Maintenance Systems, Automation, Machine Learning and
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Information Management, or related fields; Have basic knowledge of machine learning models in supervised and unsupervised learning tasks (i.e., k-nearest neighbours, Decision Trees, Neural Networks, Logistic
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, Reinforcement Learning and physical/robotic simulation for decision support may also be explored; • Contribute to the preparation of the project’s technical and scientific documentation, including scientific
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of ecosystem degradation and the aforementioned extreme climatic phenomena; (v) explore a “Machine Learning” analysis to explore the importance of other environmental and managerial factors in the spatial and
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 3 months ago
impact in the field of plasma physics, catalysis and electrolysis. By carrying out cutting-edge research, the students will not only acquire crucial skills for their future, but also scientifically
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points); b) Publications in the area of artificial intelligence, machine learning, computational simulation and multi-agent systems (maximum 5 points); c) Research experience in the project area (maximum