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Field
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) techniques developed at UEA to study the interaction of small molecules with Umami receptors overexpressed directly on the surface of live cells (2). You will thus establish ‘rules’ determining which molecular
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to the project. Degree transcripts/certificates and, if English is not your first language, a copy of your English language qualification if completed must be uploaded. Contact Details Prof. G.Tasca, giorgio.tasca
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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life-like systems from the bottom-up. We aim to enrich artificial materials with new life-like behaviour. We are based in the School of Chemistry’s new Molecular Sciences Building at the University
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of London, a dynamic institution formed from the merger of City, University of London and St George's, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School
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synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application to the analysis of time series. In particular, the project
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affect ignition behaviour. You’ll use advanced tools such as chemical kinetic modelling, multi-dimensional CFD simulations, and collaborate closely with experimental researchers. You will receive
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Fuel Rig with Five Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection, isolation, and prognostics. Machine
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suite of specialised facilities: UAV Fuel Rig with Five Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection
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engage in immersive, simulated construction tasks, while wearable sensors monitor their physical effort, emotional states, and cognitive load. Physiological and behavioural data — including eye tracking