51 development-"https:"-"https:"-"https:"-"Keele-University" PhD positions at University of Nottingham
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sustain the widespread adoption of electrical vehicles in an environmentally friendly and ethical way. A radical approach to how electrical motors is developed, combined with emerging material technology
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Studentship Information Supervisor: Vinay Shukla Subject Area: Plant & Crop Science Research Title: Root oxygen dynamics and development Research Description: The student will be part of a
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A Design Methodology for Embedding Robotics & Automation into Circular Product Development This is an exciting opportunity to undertake industrially linked research in partnership with
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for airBORNe applications” project (https://newborn-project.eu/) and develop a real-time Multiphysics Digital Twin for such a system accelerating future electric propulsion system development. Motivation
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EPSRC Centre for Doctoral Training (CDT) PhD in Digital Metal with Rolls-Royce (Enhanced Stipend) Development of Advanced Barrier Coatings for extreme environments Background Applicants are invited
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of disasters? Do you have a PhD research proposal related to this topic, or can you develop one this month? If the answer is yes to these questions, then this PhD funding opportunity for the programme of
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engineering, structural, aerodynamic & manufacturing process modelling and optimisation techniques that will transform current design & development practices. Together we will make technological advances
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sustainable chemical and biocatalytic process development. Vision We are seeking a motivated PhD student to develop a strong experimental understanding of enzyme selectivity when processing mixed biomass
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opportunity is based within the Resilience Engineering Research Group at Faculty of Engineering which conducts cutting edge research into developing modelling techniques to predict ways of improving the design
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the noise associated with near-term quantum devices. This in turn offers an exciting new dataset from which it will be possible to use machine learning to train a more accurate functional for use in density