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of optimization and generalization to inform the design of practical training algorithms. To produce high-quality publications in top-tier machine learning conferences and journals. To offer guidance and assistance
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. To collaborate with industrial and academic partners. To perform any other duties related to the research program. Job Requirements: Preferably PhD in Computer Engineering, Computer Science, Electronics
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, efficiency, parameterisation, uncertainty quantification, and/or surrogate modelling. The research may involve the use of observational, experimental, or high-fidelity numerical data to train, validate, and
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required to analyse and improve the performance of complex systems. The role offers an opportunity to contribute to high-impact research addressing the UK’s major net-zero challenges while developing
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-of-the-art analytical techniques, including High-Performance Liquid Chromatography (HPLC) and Nuclear Magnetic Resonance (NMR) spectroscopy, to characterise host–guest interactions and quantify
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perform independent and collaborative research to meet the project objectives, and to publish high-quality journal papers to promote the international reputation of the school and the University. Key
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resolution imaging techniques and flow cytometry to address key questions. The prospective candidate should have the knowledge to perform cell culture works and a willingness to learn and trouble shoot new
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months] Duties The appointees will assist the project leader in the research project - “WASTES to WINGS - Constructing a high-throughput Sustainable Aviation Fuel (SAF) research platform to facilitate zero
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the performance of complex systems. The role offers an opportunity to contribute to high-impact research addressing the UK’s major net-zero challenges while developing modelling and optimisation approaches with
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, characterization, electrochemical testing, and data acquisition into coordinated experimental workflows. The Research Fellow will contribute to the development of high-throughput and autonomous experimentation