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and emerging applications, such as multi-domain autonomy and aerial mobility. With rising risks to PNT systems from interference, spoofing, and cyber-physical attacks, unified, security-aware integrity
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infrastructure. However, the increasing application requirements and rising threats from intentional interferences, spoofing, and cyber-physical attacks expose vulnerabilities in conventional GNSS-centric systems
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of the complex physics governing the interaction between the heat source and the material. Additionally, it seeks to develop an efficient modelling approach to accurately predict and control the temperature field
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project, demonstrating their potential in thermal management and protection for battery technologies. This PhD project, building on Dr Fanicchia’s extensive expertise in coating design and thermal
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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slow sand filters. This project suits graduates seeking careers in drinking water technology, sustainable infrastructure, and low carbon process design. Drinking water production is under mounting
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system will manage and adjust the way information is used in real time. Cranfield University is a globally recognised postgraduate institution focused on applied research and strong links with industry
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revolutionizing how safety and reliability are managed throughout a system's lifecycle. This PhD project explores the application of AI in enhancing certification processes and lifecycle monitoring of safety
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This self-funded PhD research project aims to advance the emerging research topics on physics-informed machine learning techniques with the targeted application on predictive maintenance (PdM