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This is a self-funded opportunity relying on Computational Fluid Dynamics (CFD) and wind tunnel testing to further the design of porous airfoils with superior aerodynamic efficiency. Building
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complete application for your chosen PhD programme by the deadline for your department (below). Section 9 of the application asks for your funding intentions. In this section, you should detail fully all
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A PhD opportunity at the EPSRC Centre for Doctoral Training in Quantum Information Science and Technologies at the University of Sussex School of Mathematical & Physical Sciences The University
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the performance of novel, renewable, wave energy harvesting approaches. Here the research ambition is to extend the state of art from small scale sensor networks (nW’s to mW’s), towards a vehicular scale (W’s to
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process. Address blind inverse problems by defining a network to learn distortion functions from data, informing the optimization in the learning process. Refine optimization and learning strategies
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net zero goals and the future of our planet. During their lifetime, those energy storage systems can experience complex electrochemical-thermomechanical phenomena that can result in their volumetric
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real-world challenges. We work with an extensive network of industrial partners including BT, DataSparq and Tesco. Engage with our network of charitable partners Students have the opportunity to engage
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model of reaction barriers. This will enable the development of more accurate and advanced high-throughput reaction network discovery and by-product prediction. Background Typical drug molecules can
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formation. Complementing these experimental efforts, Computational Fluid Dynamics (CFD) simulation will be employed to interpret CRUD build-up measurements, identify key phenomena influencing CRUD deposition
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October 2025 start ONLY For January and April starts please use the relevant application. This form is only to be used by those self-funded applicants seeking a place on a research degree programme at