26 power-system-"https:"-"https:"-"https:"-"Fraunhofer-Gesellschaft" PhD positions at University of Warwick
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Research area and project description: AI data centres are digital engines, yet ~30% of energy is wasted as heat in power conversion and distribution. Directly addressing the UK’s Clean Power 2030
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operation. This is an exciting PhD project with industrial collaborators at the intersection of power systems, artificial intelligence, and mathematical modelling. The project is well-suited to students with
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is essential to maintaining UK leadership in power electronics and supporting strategic supply chain resilience. This PhD project will focus on the design, modelling, and optimisation of ultra-high
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validation methods employed for battery systems created for electric vehicles, aerospace or stationary storage. This PhD will aim to deliver a new validated methodology for scientifically assessing lithium-ion
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of metallic systems, fundamental metallurgical phenomena as well as basic characterisation. A burning passion and demonstrated ability of independent academic research and contribution to scientific
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About the project: Extreme Space Weather: Modeling Rare Solar Storms and Their Impacts on Earth Supervisor: Dr Ravindra Desai, University of Warwick Space weather is driven by eruptions of plasma
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into electrical energy, crucial for sustainable power and waste heat recovery. Their efficiency is measured by the figure of merit, ZT. Achieving high ZT requires a delicate balance: high electrical
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of spins that could form the basis of future low-power data storage devices. However, real skyrmions are three-dimensional and can twist, stretch, or deform when trapped by material defects - behaviour
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manufacturing, yet their performance is fundamentally limited by our inability to precisely control particle alignment and microstructure during fabrication. Existing methods—such as magnetic or electric field
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designed specifically for the spatial and sequential structures inherent in XCT projections and reconstructed volumes. The goal is to achieve a 60-80% reduction in data size without compromising