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using ISO 14040/44-compliant lifecycle assessment frameworks. Guided by the principles of cradle-to-cradle design, disassemblable product architecture, and closed-loop polymer flows, the research will
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us to run large numerical simulations with billions grid points on mixed computer architectures including CPU and GPU machines. A current project is preparing the code set for the next generation of
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Programme: Hybrid CFD and process simulation for process intensification of post-combustion CO2 capture School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Prof
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consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will train the next-generation of doctoral carbon champions who are renowned
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rate). An additional allowance will be provided to contribute towards consumables, equipment, and travel related to the project. Number Of Awards ReNU+ is a unique and ambitious programme that will
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the PhD student in high-performance computing, computer programming, applied mathematics, fluid mechanics, mathematical modelling and data analysis for large datasets -of the order of 100 Terabytes
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the development and implementation of machine learning (ML), computer vision (CV), large language models (LLMs), and vision-language models (VLM) to automate data extraction and interpretation for productivity
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piezoelectric composites and material architecture to achieve improved electromechanical coupling and spatial resolution would be important. In addition, they should have experience in sensor array readout
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The funding provider: Health Data Research UK Subject areas: Wider Data Science Field, Maths and Computer Science Project start dates: 1st October 2025 ** (Please see the note below regarding
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collaborative studentship between the University of Edinburgh and the National Quantum Computing Centre (https://www.nqcc.ac.uk ). The position will be registered and hosted at the University of Edinburgh and