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research activities. The applicant will have obtained or be close to obtaining a PhD in Mechanical Engineering or Materials Science. Appointment at Research Associate level is dependent on having a PhD
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of Oxford. Unpaired electron spins are ubiquitous in materials and devices for optoelectronics and solar energy technology and play a crucial role in the fundamental photophysical processes at the basis
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MLPs to run classical MD simulations and characterise thermal transport. This PhD project will be based within the School of Engineering, University of Edinburgh. This PhD project will be supervised by
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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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engineering or another relevant field applicable to the measurement technology development. For this position, we are unable to consider significantly different backgrounds, such as biology- and simulation
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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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Engineering (PhD) Eligibility: UK Students Award value: Home fees and tax-free stipend £20,780 - See advert for details Project Title: Machine Learning and Optimisation-Based Intelligent Substation Design in
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); The applicants may have a background in any aspect of Materials Science, Metallurgy, Physical science or Engineering. A copy of your undergraduate/Postgraduate degree certificate(s) and transcript (s); Names and
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and manufacturing methods. The Centre's contributions to industry are demonstrated through its extensive MSc and PhD research initiatives and its ongoing technology development programs in large-scale
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Award Summary 100% home tuition fees and £20,780 annual stipend (25/26). International candidates must cover the fee difference. Overview We invite applications for a fully funded PhD at Newcastle