49 postdoctoral-image-processing-in-computer-science PhD positions at Cranfield University
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engineering or a relevant area. An MSc degree and/or experience and good knowledge in gas turbine theory, thermodynamics, Machine Learning, and computer programming will be an advantage. Funding Sponsored by
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doctoral training programme dedicated to academic research in space propulsion. R2T2 PhD programmes are already underway at nine UK universities, and the programme overall is centred on the Westcott facility
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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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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, computer vision or flow measurement background. Prior experience in computational modelling is beneficial, but not mandatory. Similarly, experience of computer coding in some form or any discipline is also
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-based solutions (NbS) for water and wastewater treatment. The research will explore sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The
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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
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novel methodology for designing and assessing highly integrated fuel systems for ultra-efficient propulsion systems fuelled by SAF. The assessment will be done in terms of performance, operation and
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the subject area and continues to expand its research horizons. It plays a pivotal role in the £65 million Digital Aviation Research and Technology Centre (DARTeC), leading advancements in aircraft electrification
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evaluation. Prognostics is an essential part of condition-based maintenance (CBM), described as predicting the remaining useful life (RUL) of a system. It is also a key technology for an integrated vehicle