29 affective-computing-"https:"-"https:"-"https:"-"Bath-Spa-University" PhD positions at Cranfield University
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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industries located in Kuwait. The framework will connect productivity, cost, equipment workability, and product quality. The utilization of near real time equipment inspections and its impact on production
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Resilience (WIRe). The WIRe programme offers a bespoke training programme in technical and personal skills, access to world-leading experimental facilities. The successful candidate will also have the
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requirements A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, electrical, chemical, computing, and manufacturing) with a minimum 60% mark in
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Advances in computing, experiments, and information will continue to reshape engineering in the next decade. This PhD position will nurture a multidisciplinary innovator with the tools to unravel
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via joint activities with EU and UK cybersecurity hubs, preparing you for careers in trusted electronics, AI security, and national critical infrastructure protection. Graduates from this programme will
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A funded PhD studentship is available within the Autonomous and Cyber Physical Systems Centre at Cranfield University, Bedfordshire, UK. As aerospace platforms go through their service life, gradual performance degradations and unwarranted system failures can occur. There is certain physical...
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This PhD opportunity at Cranfield University invites candidates to explore the integration of AI into certification and lifecycle monitoring processes for safety-critical systems. The project delves into areas such as AI-driven verification, predictive maintenance, and compliance assurance,...
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves