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in complex geometries or constrained spaces relevant to in-vessel fusion applications. To support this work, the candidate will develop rigs and carry out experimental investigations into the emissive
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the integration of robotic systems equipped with adaptive grasping mechanisms and advanced locomotion strategies, enabling them to navigate and interact with complex geometries in microgravity environments
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photorealistic game worlds. To achieve this goal, we need advances in many areas, from light transport, sampling, geometry and material representations, and computationally efficient algorithms to display
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maintenance. 4. Automated Design Optimization: Reinforcement learning and genetic algorithms will be applied to optimize CFDST geometries and material configurations for maximum efficiency and durability. By
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benefit society by advancing technologies that will underpin the design of the next generation of transport aircraft. Specifically, you will develop, test, and industrialise algorithms designed to simulate