18 design "https:" "https:" "https:" "Lawrence Berkeley National Laboratory Physics" PhD positions at University of Warwick
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About the project: Machine learning accelerated Inverse Design of Graphene Nanoribbons for Green Energy Supervisor: Dr Sara Sangtarash, University of Warwick Thermoelectric materials convert heat
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There exists an inherent variability in how lithium-ion batteries fail – an event commonly referred to as “thermal runway”. This uncertainty drives additional cost and complexity into the design and
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stacking error and removes the options for easy disassembly for repair, replace or recycle. In this project modification of the cell end cap design is to be investigated through FE analysis, prototype build
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, you will pioneer new routes to “designer” composites for sensing, manufacturing and resilient infrastructure. Advanced polymer composites underpin lightweight transport, renewable energy technologies
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Modulation and Imaging Experiments: Data Analysis and Design Optimisation: Scholarship: The award will cover the UK tuition fee level, plus a tax-free stipend, currently £21,805, paid at the prevailing UKRI
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on the design and modelling of ultra-high voltage IGBTs, thyristors, and SiC devices for HVDC and energy systems. Embedded within the EPSRC Rewire network, the project strengthens UK capability in high-voltage
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candidate to join the UKRI Future Leaders Fellowship (FLF) research project of Dr. Zsuzsanna Koczor-Benda on “Quantum embedding for functional nanodevice design” in the Department of Chemistry at
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) software using PyTorch, making the tools immediately accessible to the wider scientific community. The student will work across the University of Warwick (WMG) and the Harwell Science and Innovation Campus
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processing using a state-or-the-art Gleeble HDS-V40 to test the materials behaviour to stress and recrystallisation kinetics at temperatures around 1400C. Alloy development to understand / design how
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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