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Field
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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load emulation, surface tribology and lubricants, contact mechanics or dynamical phenomena. This is an opportunity to work within a world-class multidisciplinary team within the Engineering Systems
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to reduce AC losses and boost power density. Today's modelling tools are not yet equipped to fully explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers
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that are difficult or unsafe to access. This project proposes the development of a soft robotic arm capable of navigating into intricate industrial structures and which can be integrated into a legged inspection robot
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manufacturing methods, such as autoclave or oven curing, are energy-intensive, costly, and often impractical for large-scale or complex structures. This PhD project aims to develop next-generation, energy
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Cell wall modification in plant immunity and development Structural roles of the cell wall in stomatal movements (Carroll et al., Current Biology 2022). The role of epigenetics in plant immune memory and
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machine structures, together with AI-driven optimization frameworks for diverse applications while considering LCA metrics. The success of this project could serve as a model for other energy-related
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of the structure and use of routinely collected cancer data. In this role, the postholder will act as a liaison between the National Disease Registration Service and the Departments of Public Health
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audiences; enthusiasm to be part of a team and actively contribute to a dynamic, engaging, and collegial academic environment. Our offer A position for one year, with an extension to a total of four years
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dynamic environments, including narrow spaces and interactions with unfamiliar objects. This project aligns with Rolls-Royce’s technical needs for developing soft robotic solutions to enable in-situ/on-wing