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allow you to explore the fundament physical limits of the technique and to create new image reconstruction algorithms. This project offers the opportunity to produce new techniques in imaging physics
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the utility and the robustness of different explanation strategies. A large focus of this project will be on leveraging novel and interpretable approaches in applied domains such as algorithmic fairness and
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the timing of irrigation develop detection algorithms to identify signals in cloud and precipitation properties during periods of irrigation activities analyse interactions between irrigation, clouds, and
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that shape the design of these circuits. The lab is dedicated to medical algorithmics on the applied research front, emphasising technologies implementable within hospitals. Notably, the lab’s medical image
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Technology, and Power and Energy Measurement Systems. Within smart grids, the focus is on modelling and optimisation of modern distribution networks and microgrids, and energy management systems for seamless
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Physics graduates with a strong background in Fluid Mechanics and Heat Transfer. The work will involve the use of flow diagnostics techniques and post-processing algorithms. It will also require
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microbial communities. In this role, you will develop hybrid species distribution models that combine climate and landscape data to predict how microbial taxa niches shift under changing land use and
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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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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