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Field
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Research Assistant in Classics and Archaeology About the Role The duties will include: Observing a series of training sessions, in-person at University of Nottingham. Assisting with the design of a
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—remains a critical challenge. This project will focus on designing AI-driven cognitive navigation solutions that can adaptively fuse multiple sensor sources under uncertainty, enabling safe and efficient
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developments such as novel algorithms to support logistics operations, novel automation approaches or the design and development of new digital support tools for logistics providers. Significant flexibility
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Partnership at the University of Cambridge. This programme is a collaboration between industry and academia, now in the final 24 months of a 60-month effort. The programme integrates research and innovation
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spread over five months (October 2025-February 2026). The duties will include: Observing a series of training sessions, in-person at University of Nottingham. Assisting with the design of a schedule of
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and deterministic AI outputs is critical. This requires robust design principles and architectural changes to reduce variability and integrate smoothly with industrial control systems. Enhancing
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aims and objectives are met. Working closely with the supervisory team, develop and plan research objectives. Present information on research progress and outcomes to, for example, project lead, funding
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language requirements and profile levels . Funding: Minimum tax-free stipend at the current UKRI rate is £20,780 for 2025/26. For eligibility and residence requirements please check the UKRI UK Research and Innovation
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focus will be on biomechanics, image processing, machine learning (ML), artificial intelligence (AI), and metrology, the student will also contribute to the co-design of cadaver experiments and data
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
and reasoning techniques to support predictive maintenance and asset health monitoring •Design feedback mechanisms that deliver interpretable insights (e.g. alerts, recommendations, confidence scores