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will be developed using the OpenFOAM toolkit. A modelling workflow will be created, and then used as the basis for the optimisation, potentially using tools such as Bayesian Optimisation. In addition
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optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in
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Bayesian inference framework for identifying complex aerospace systems combining with limited experimental data. It can be also used to quantify uncertainties from experimental testing, significantly
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to develop an SDT that simulates real-time system operation in a dynamic virtual environment. 3. Online Implementation: Deploying the SDT on an evolving online platform, continuously updated with new data and
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of managing own workload, sticking to deadlines and the ability to constantly update knowledge Appointment at Research Associate level is dependent on having a PhD. Those who have submitted but not yet received
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at the DEEP lab at Harwell. The project aims to provide a detailed understanding of plasma deposition affecting operational utility of SuperMagdrive propelled launcher kick stages; leading to an updated design
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, for example, parameter quantization, learning a student LLM from a teacher LLM for down-stream tasks, and design of reversible LLMs. A reversible LLM allows for online back-propagation when updating the model
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£22,780 in 2025/2026, updated annually) and tuition fees are waived (UK/Overseas). As part of the scholarship, they will be required to undertake teaching and related duties in the Business School of up
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. Interested applicants should contact Dr. Tim Tang via email tim.tang@manchester.ac.uk with an updated CV. Suitable candidates will be asked to complete the electronic application form at The University
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submitted but not yet received their PhD will be appointed at Research Assistant level, updated to Postdoctoral Research Associate level once their PhD has been awarded. The salary range for Research