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will examine how the configuration, connectivity and condition of these dynamic water systems, and their surrounding land cover, influence environmental buffering, biodiversity and social benefits
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and improve monitoring practices, and the social factors that influence their uptake. This studentship offers a unique opportunity to engage in ground-breaking research with practical applications
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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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, 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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the intersection of ecology, machine learning, and sustainable land management, the research will combine field data collection, deep learning model development, and stakeholder co-design to support biodiversity