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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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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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the availability and distribution of shaded pedestrian routes in Reading, with the aim of identifying priority areas for shade provision to support equitable and heat-resilient urban mobility. Green infrastructure
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well as in the implementation of multiple use cases utilizing both laboratory prototypes and commercial Quantum Key Distribution (QKD) systems. These use cases will be demonstrated over existing fiber-optic
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-based quantum communication applications. Communication protocols such as quantum key distribution (QKD) represent a promising solution for ensuring future communication security, and satellite-based
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build the sustainable companies and societies of the future. Pervasive and Mobile Computing (PMC) research subject addresses fundamental challenges in distributed systems and mobile networks, enabling
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build the sustainable companies and societies of the future. Pervasive and Mobile Computing (PMC) research subject addresses fundamental challenges in distributed systems and mobile networks, enabling
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spatial distributions of active phases across multiple length scales. The PhD student will collaborate with international partners to study the evolution of crystalline and amorphous domains in the hybrid
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algorithms, validated navigation architectures, and new insights into next-generation intelligent mobility solutions. The student will undertake two industry placements at Spirent, use high-tech simulation