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Field
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elements like Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) to secure hardware components. Embedded Trust Protocols: Design protocols that establish and maintain trust within
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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/ physics/ meteorology/ engineering/ biology. Experience in a computer programming language (e.g. Fortran, Python). A general understanding of the importance of the scientific method is essential. A previous
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they meet the following criteria: A first-class honours degree (or equivalent) in Engineering, Materials Science or Physics Excellent written and spoken communication skills in English Strong mathematical and
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, or physics, and will demonstrate a willingness for experimental fieldwork and data analysis. This PhD offers a unique opportunity to contribute to frontier research in atmospheric chemistry, with
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. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make
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with a background in mechanical, aeronautical, automotive, civil / industrial and/or software engineering (or similar) and/or mathematics and/or physics. The ideal candidate will have a solid background
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, embedded intelligence, and adaptive cyber-physical systems that operate safely under uncertainty and dynamic conditions. This PhD at Cranfield University explores the development of resilient, AI-enabled
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with a first class or upper second-class degree in engineering, physics, applied mathematics or a related field. A solid foundation in fluid dynamics and heat transfer, and experience with computer
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techniques and advanced sampling methods to bring a significant advancement in reducing high-fidelity runs to accelerate the engineering design, validation process and improve the robustness of the prediction