Sort by
Refine Your Search
-
predictive accuracy and prohibitively long computational times, making them unsuitable for real-time process control. Artificial intelligence (AI) models present a promising alternative by addressing
-
targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
-
at international conferences and build a professional network across academia and industry. Development of expertise in cutting-edge experimental techniques, computational modelling, and interdisciplinary
-
of novel AM materials on corrosion response of key component and develop a model to predict their behaviour. To address the goals set for tackling international climate change, the power sector needs
-
intensive training in energy modelling, AI-accelerated optimisation, and lifecycle-aware computing. Whether working on smart mobility, sensor nodes, or autonomous platforms, you’ll be contributing to a new
-
Resilience (WIRe) , a prestigious collaboration between Cranfield University, the University of Sheffield, and Newcastle University. The WIRe programme offers bespoke training that hones both technical and
-
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
-
. The enhanced image quality will support earlier and more reliable detection of eye diseases. Combining artificial intelligence with mathematical modelling, this non-invasive, cost-effective approach has
-
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
-
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