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Field
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apply. Understand ML/DL frameworks such as TensorFlow and PyTorch. Familiar with version control systems such as Github, Git, etc. TOEFL, IETLS or other certificates that can prove your English level
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control strategies. Current steel processing typically has very tightly controlled processes with little variability and control approaches optimised to minor changes. The combined challenges of cost
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. The research combines robotics, computer vision, artificial intelligence, machine learning, control systems, and medical robotics to solve one of the most challenging problems in modern automation. Project
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understanding of how light can be used to control polymer formation and structure. A key focus of the project will be chemical recycling. You will develop photocatalytic approaches to selectively break down
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vehicles, robust control, and experimental validation. The work will be carried out in close collaboration with the partner team at Poli-USP, whose expertise covers robust control, digital control
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strategies that maximise information gain under resource constraints; RL-based approaches for sequential intervention and control; and robust learning methods that adapt to incomplete observations, changing
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histopathology and clinical information to learn robust cross-modal representations for diagnostic prediction. It pursues two integrated objectives: (i) to develop generative and explainable AI approaches
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: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety: Ensuring robust alignment and safety in multi-agent LLM systems Efficiency: Streamlining large-scale model
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microgrids integrating intermittent renewable energy sources (solar, wind), storage systems (batteries, hydrogen), power electronic converters, and controllable loads. These complex cyber-physical
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and hardware security assurance for embedded systems by combining advanced side-channel analysis, fault-injection techniques, AI- and machine-learning-assisted analysis, robustness evaluation, and