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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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-edge advancements in automated drug discovery through the integration of high data-density reaction/bioanalysis techniques, organic synthesis, laboratory automation & robotics and machine learning
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with programming (Python, MATLAB), background in aerospace, computer science, robotics, or electrical engineering graduates, hands on skills in implementation of fusion/learning based techniques in
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Supervisory Team: Dr N.C. Townsend, Prof A. Murphy PhD Supervisor: Nick Townsend Project description: In this PhD project you will explore novel wave energy harvesting systems for maritime robotic
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reusable launchers, autonomous robotics, and advanced materials could redefine how we design space structures. The ability to remotely assemble orbital systems from multiple launcher payloads would allow