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research has focused on improving the performance, efficiency, and autonomy of such systems, their empirical security assessment remains underdeveloped, representing a growing and critical gap. Recent
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guardrails inspect everything in plaintext and offer weak formal assurance. This PhD asks how to build AI services that remain useful while enforcing such constraints and protecting sensitive information. Open
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Phd Studentship in Computer Science: Empirical Security Assessment of AI Decision Engines in Cyber-Physical Systems Award Summary 100% home fees covered, and a minimum tax-free annual living
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, machine learning and Quantitative Microbial Risk Assessment Microsimulation modelling, generating evidence directly relevant to national food safety policy. You will join a PhD student cohort with NIHR