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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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learning, control theory, and embodied autonomous systems. The successful candidate will contribute to the development of learning-based control methods that are not only high-performing, but also safe
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-of-the-art, high performance computing cluster You would join the Aerospace Environmental Impacts Simulation (AEIS) group The opportunity to continue your career at a world-leading institution and be
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responsibilities and duties include: Designing research framework and methodology and performing operational and functional testing of the experimental system to a high standard. Building positive relationships with
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
to cutting-edge facilities including High-velocity impact testing, Advanced composite manufacturing labs, X-ray computed tomography and High-performance computing resources for AI model training This project
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Materials, mastering scientific machine learning, uncertainty quantification, and high-performance computing. Your models will inform fusion design and advance AI-for-materials. Perfect for physics, maths
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PhD studentship in Computer Science - Dynamic Validation of AI Systems in Digital Twins: A Real-Time Safety Framework for Critical Infrastructure Resilience Award Summary 100% fees covered, and a
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transport, high-performance mechanical seals are essential. These seals prevent gas leakage by maintaining a sub-micron-thin layer of hydrogen between a rotating ceramic face and a stationary face. The
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, limited predictability and slow process optimisation. The PhD sits within an interdisciplinary research environment that combines laboratory experimentation with mechanistic and computational modelling
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tax-free stipend for Home and Overseas students of £25,726 per year. Applications Close: 28th February 2026 Start Date: 28th September 2026 (contract duration 4 years) Railway performance across the UK