44 phd-position-in-image-processing PhD positions at Cranfield University in United-States
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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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Cranfield University and Magdrive, offer a fully funded PhD position under the umbrella of the R2T2 consortium to study the optimisation of their thruster for a kick stage. R2T2 is a UKSA-funded
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(PhDs under this scheme are for a duration of four years full time). At the end of the project the successful applicant will be very well positioned to have a highly successful career in the water sector
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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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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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
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project
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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
professional and transferable skill development, preparing graduates for careers in aerospace, engineering, and digital innovation. Throughout the PhD, the student will develop a broad set of skills, from
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This PhD opportunity at Cranfield University invites candidates to pioneer research in embedding AI into electronic hardware to enhance security and trustworthiness in safety-critical systems