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of Artificial Intelligence in Green Algorithms Research line / Scientific-technical services: Development of algorithms that are energy-efficient. Project data Title: UDC-Inditex Chair of Artificial Intelligence
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to): Transparency and contestability in AI Accountability in algorithmic infrastructures Technical mechanisms for evaluating and auditing AI systems Governance of open-source and general-purpose AI models Data rights
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electronic converters are required to connect renewable energy sources and energy storage systems to the power network. These converters employ sophisticated control algorithms that must simultaneously achieve
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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novel sensing approaches to combine with machine learning algorithms to solve real-world problems in food manufacturing. You will have sound knowledge in electronic engineering, embedded systems design
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on Education and AI (NOLAI). You will create methods to predict energy consumption, create energy labels for algorithm scalability, and guide implementers in choosing more efficient algorithms. Ready to make AI
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contributions to standardisation efforts. Your role This fully funded PhD position focuses on exploring and developing hybrid quantum-classical algorithms to tackle sustainability challenges. Key areas include
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advanced statistical machine learning, reinforcement learning, and gen-AI-driven decision models for supply chain and operations optimization. • Design scalable algorithms for demand forecasting, risk
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approach could resolve this issue and we could use obtain data-driven models using machine learning algorithms such as artificial neural networks, reinforcement learning, and deep learning. A typical caveat