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Field
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data requirements, and lower costs for large-scale modelling tasks. PINNs enhance predictive capabilities and efficiency by combining data-driven methods with physical principles. Unlike traditional
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the computational activities in a large closed-loop collaboration that includes computational, biotechnological and automation activities, requiring a solid understanding of the different areas involved in
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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algorithm. Design methods: Develop novel control methods for power electronic converters feeding electric machine Simulation: Learn advanced simulation tools such as Ansys to simulate and analyze the effect
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communication systems which have different performances under different channel conditions. - Providing high-speed underwater communication, for industrial applications in real time underwater communications
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detection and classification algorithms using measured and/or simulated data, such as current pulses from cable faults (breakdown), partial discharges and external noise. In addition to being part of
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within a species, going beyond the limitations of single-reference genomes. By integrating multiple genomes from different individuals or populations, pangenomes can provide a more comprehensive
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international research environment covering a wide variety of research areas, such as algorithms and data structures, machine learning, computer graphics and vision, database systems, artificial intelligence