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qualifications and experience in Analytical Chemistry, Chemical Engineering, Biochemistry, or a related field. Strong and proven record in academic writing and publication in recognised journals. Extensive
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travel. Publish findings in high-impact journals and present at international conferences. Requirements: PhD or equivalent qualifications and experience in Analytical Chemistry, Chemical Engineering
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the full complexity of fabrication processes and enable optimisation before physical manufacturing begins. This project aims to develop advanced deep learning models capable of predicting fabrication
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optimisation before physical manufacturing begins. This project aims to develop advanced deep learning models capable of predicting fabrication outcomes and guiding fabrication recipe optimisation. By learning
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on understanding the aerodynamics and aeroacoustics of overlapping propeller systems. This project will involve high-fidelity flow and noise measurements, combined with semi-analytical predictive models
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with semi-analytical predictive models, to establish new physical principles for designing high-efficiency, low-noise multi-rotor configurations. You will have access to state-of-the-art facilities
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on patient care through improved diagnostic pipelines, integrative analytics, and data‑driven insight. As fitting with a Research Fellow or Senior Research Fellow, you will: Drive innovative research
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discipline. Applications will also be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. Applicants should have excellent experimental and analytical
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the mentorship of leading experts in one of the following priority research areas: Research area 1: Intelligent Structural Optimization using Physics-Informed Reinforcement Learning Research area 2: AI-Enhanced
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for light–matter interaction in hyperuniform disordered plasmonic structures, including electromagnetic modelling, optimisation of metal–dielectric–metal resonators, and physics-informed machine-learning