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network attractors, funded by The Leverhulme Trust. This is a brain inspired project in the field of Neurodynamics. Networks of oscillators are ideal candidates for modelling patterns of functional
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Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering
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applications, including 5G/6G wireless communication systems, satellites, radars, and drones. A key focus of the project is to create low-cost antennas and mm-wave devices capable of delivering unique
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applications, including 5G/6G wireless communication systems, satellites, radars, and drones. A key focus of the project is to create low-cost antennas and mm-wave devices capable of delivering unique
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learning from sensor feedback. This PhD aims to develop novel algorithms for Artificial Intelligence (AI) driven continual learning via reinforcement learning (RL), incorporating mechanistic knowledge
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Bragg sensors. Demonstration for evaluating the developed snake robot and its navigation and localisation strategies. We are seeking talented candidates with: First or upper second-class degree in
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robots. We currently imagine these to be soft materials that dress both human and robot bodies. Embedded sensors will capture data about mutual touch. Embedded actuators will deliver haptic feedback
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Background Network Rail operates several telecom networks which provide connectivity for various signalling systems. Therefore, the performance of telecoms assets is integral to how the railway system operates
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to produce anti-counterfeit markings, dye-free colour images, humidity and chemical sensors, anti-glare coatings and optical filters. This project will develop additive manufacturing of devices with actively
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properties in a few compositional series of network glasses, from which key compositions to study in the molten state will be selected. Improved understanding of melt structure will have a major impact on