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Field
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human capital, finance and investment, macroeconomics, regional and international comparisons, public policy, and the productivity challenges created by the new technologies and the transition to net-zero
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point of this project is the opportunity for the successful applicant to work within the Centre for Computational Engineering Sciences, a leading hub for research and education in computational methods
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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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Type of award Studentship Managing department School of Social Sciences Value Tuition fees An annual maintenance stipend (£19,237 per annum for 2024/25) A research training support grant Specified
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This is a fully funded project for home students, funded by NTR-Net. The funding will cover tuition fees and provide a tax free (depending on circumstances) stipend based on the UKVI rate (£19, 237
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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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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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network and enhancing their career prospects. From this experience, the student will gain a wide range of transferable skills that will significantly enhance their employability. They will develop strong
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safeguarding animal, human and environmental health. The candidate is expected to have a good knowledge of animal science, nutrition, physiology and biochemistry. It is desirable that the candidate has good
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. While a background in materials science is preferable, it is not a prerequisite, as there are opportunities for retraining. This ensures that the project is accessible to individuals from diverse academic