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recovery in critical applications, including aerospace, healthcare, and industrial automation. Research Focus Areas: Predictive Analytics for Fault Detection: Develop AI models that predict potential system
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/emissions modelling preferred but not required Creative problem-solving skills and ability to work independently *Candidates with a PhD in other disciplines may be eligible if they can demonstrate exceptional
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This PhD opportunity at Cranfield University explores how next-generation AI models can be embedded within resource-constrained electronic systems to enable intelligent, real-time performance
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, balancing efficiency and sustainability in AI deployment poses a significant challenge, calling for advances in model design and training to reduce environmental impact while maintaining high performance
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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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prognostic models for filter degradation. Integrated Drive Generator (IDG) Rig: Simulates the operation of an aircraft's IDG, used to investigate fault detection, diagnostics, and prognostics in power
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energy; thereby minimising farming’s environmental impact. AI machine learning offers a new expedient method of developing control systems for tasks that would be difficult to manage using classical
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rely on unsustainable materials and on carbon-intensive manufacturing processes. This is posing major environmental and ethical challenges. The project will motivate the PhD student to develop next
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This project aims to bridge the gap between technological advancements and their integration into societal and environmental systems by shifting from a product-centric to a service-oriented approach
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experimental methods to improve them, alongside developing new approaches to enhance these properties. External environmental factors, such as humidity, pressure, and temperature, will also be key variables