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+ Quantum Information Science + Quantum Optics + Theoretical Physics , Quantum Sensing , Quantum Sensors , Quantum Simulation , Quantum Technology , Quantum Transport , Quantum transport in low-dimensional
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of developing a computational model to simulate hydro-sedimentary dynamics and morphology between restored patches to explore conditions favourable for restoration. Validated with data on vegetation cover and
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the structure present in food systems dictates functional aspects such as digestion and release of nutrients. Working alongside other postdocs and students focused more on biological aspects of these processes
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modeling to simulate the pavement response under different loading conditions. The research will support improvements of the existing specification for the maximum authorized axle load and mass of vehicles
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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Fixed-term: The funds for this post are available for 12 months A position is available for a Postdoctoral Research Associate (Postdoc) in the forthcoming Aspirational Computing Lab in
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. The successful candidate will work on developing new theoretical models and computational methods to investigate the fundamental limits of polariton-assisted inelastic electron tunneling in tunnel junctions made
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), we aim to close this gap, by developing AI models and tools for tabular data, to help organizations, of any size, domain, and level of data literacy, get insights from structured data, efficiently
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) and the University of Warwick seeks to develop flexible digital twin models that will enable novel, integrated solutions to the decarbonisation of heating and cooling on large industrial and commercial
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the physical and biological pumps during rapid climate transitions (e.g., the last glacial period and Holocene) using sediment records. Our data will be used in marine carbon cycle models to predict