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project aims to address this gap through the development of a rigorous empirical framework for evaluating the security robustness, failure modes, and operational risks of AI decision engines in cyber
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cells with tailor-made error-correcting codes. The successful candidate will combine computational design with laboratory work, developing DNA/RNA systems, molecular circuits, and experimental assays
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identifies new health and care innovations, it rarely considers factors influencing implementation. The PhD will be co-developed with the student and examine how implementation considerations can be embedded
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, reproducible, and comparative empirical assessments across classes of AI decision engines. This PhD project aims to address this gap through the development of a rigorous empirical framework for evaluating