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Field
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theory and computational methods to understand the nature of the confinement mechanism of QCD. Funding duration: 3 years Funding Comment This scholarship covers the full cost of tuition fees and an annual
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industries, including: Aerospace: Faster, more efficient design and real-time condition monitoring for safer aircraft and spacecraft. Civil Engineering: Real-time health monitoring for bridges and skyscrapers
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Project Overview This PhD project is part of an Innovate UK-funded research programme focused on developing a novel ammonia-fueled engine and generator set (genset) demonstrator for harbour and
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machine-learning surrogate models capable of delivering near-DFT (density functional theory) accuracy in just a few CPU seconds per structure. This approach will enable the high-throughput screening of tens
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synthetic groups at the University of Cambridge, University of Oxford, Hasselt University, Chemnitz University of Technology, Princeton University and Georgia Tech. Who we are looking for: Motivated students
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PhD in the Engineering Hydrogen NetZero (EnerHy) CDT which is a new EPSRC-funded Centre for Doctoral Training (CDT) focusing on research and training in the areas of Hydrogen and Wind Energy. The
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the recording of substrate-borne vibrations produced by earthworms (and other invertebrates) in situ. To fully exploit this emerging technology there is a need to unravel the meaning within the data. As such
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their practical deployment. The Project: This PhD will develop the science and engineering required to overcome these bottlenecks, with the following objectives: • Uncover the mechanisms driving enhanced hydrogen
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
system health monitoring, and more efficient maintenance planning. Digital twins offer a powerful foundation but must evolve beyond simulation to truly support engineering decisions. This PhD will develop
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your suitability with evidence of the following: Have backgrounds in computer science (or engineering), system engineering, or physics/mathematics. Knowledgeable in machine learning techniques (had