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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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qualitative data acquired through focus groups and interviews with regulators, manufacturers and engineers, and deriving analytic insights into material perceptions and values. In addition, they will oversee
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, finance, and healthcare, where data integrity and system reliability are non-negotiable. This PhD project addresses the integration of robust security measures within AI-enabled electronic systems
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of the GAG biosynthetic machinery Applying novel GAG analytical technologies to investigate how changes in GAG structure and organisation drive and/or respond to shifting developmental stages. Working
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mitigating jamming and spoofing threats in real-time. Integration of Trusted Execution Environments (TEEs): Investigate the use of TEEs to create secure zones within embedded systems, facilitating secure data
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scientific discipline. • First-rate analytical and numerical skills, with a well-rounded academic background. •Demonstrated ability to develop precision mechanical devices/mechatronics •Ability to develop kinematic and
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health management (IVHM) system that leads to enhance safety, reliability, maintainability and readiness. Generally, prognostics models can be broadly categorised into experience-based models, data-driven
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for global industries, all while collaborating with experts in the prestigious International Systems Realisation Partnership. Furthermore, the student will gain invaluable skills in data analysis, problem