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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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. Funding This is a self-funded PhD. Find out more about fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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multispectral and/or SAR data to improve biomass recovery estimations, measuring biases between GEDI and EO time-series estimations, developing customised hybrid neural networks (e.g., CNN-LSTM for capturing both
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Birmingham City Council to start in October 2025. This PhD project aims to investigate how changes in travel modes can contribute to achieving net-zero emissions in urban transport. Specifically, it will
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first-class or upper second-class honours degree in mechanical engineering or a related subject. This studentship will attract a stipend of £20,480 for four years. The position arises from an engineering
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at Faculty of Engineering. Vision We are seeking PhD student that is interested in high pressure reactor systems that can be used to produce high value molecules from lignin rich wastewaters that arise from
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to the Net Zero targets. In consultation with the wider CDT community, the work will also include the development of a roadmap for the maturation of the technology and the processes required to have it adopted
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. The project will be part of the activities of the Constellium University Technology Centre (UTC) established with BCAST. The successful candidate will have the opportunities to interact with researchers in
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access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after the PhD. The Faculty has outstanding facilities and works in
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Maguire. Training and Mentoring: You will learn a multidisciplinary set of practical skills including reaction kinetics, enzymatic chemistry, analytical techniques (e.g. NMR / fluorescence / UVVis