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Field
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modelling. This exciting project involves the application of innovative methods such as high-throughput experimentation to expediate the syntheses (and bioanalysis) of life-saving pharmaceuticals
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this, there are further sub-objectives during the investigation to achieve this goal: Predict thermal warpage effects on a supersonic intake at different flight times, coupled to a numerical model for the downstream
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(i.e. red agents). However, due to a fragmented market, rapid technical developments, and nascent research the extent of capabilities and optimal solution architectures are not well understood. Current
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
placement with Rolls-Royce. The research focuses on AI-driven digital twins, using large language models and knowledge graphs for predictive maintenance in aerospace systems. Aerospace systems generate vast
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project will develop novel methods for modelling and controlling large gossamer satellites (LGSs), so that they can be reliably utilised in space-based solar power (SBSP) applications. The candidate will
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the field of Modelling and Simulation (M&S), with a focus on biomechanics, biofluid dynamics, and machine learning applications in healthcare. Specifically, it addresses the simulation of cerebral blood flow
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. A non-deterministic AI machine learning model for the identical task would not offer this demonstrability or, critically, the repeatability of classical algorithm-based systems. Furthermore, there is
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: Coordination Layer: Formulate passivity-based conditions that guarantee agents—modelled as general nonlinear systems—synchronize their outputs or follow desired collective patterns purely through local
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molecular biology, quantitative imaging and biophysical approaches to investigate cell shape changes in cultured cells and in vivo. Current projects in the lab include investigating the regulation
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(Applications) through reliable quantum advantage assessment. Project Description The project addresses the critical need for reliable, scalable verification and benchmarking schemes in quantum computing. Current