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Field
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powerful framework for decentralised machine learning. FL enables multiple entities to collaboratively train a global machine learning model without sharing their private data, thus enhancing privacy
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advantageous. Familiarity with mathematical modelling of power electronics circuits is also desirable. Funding Further information and other funding options . Informal Enquiries: s.neira@ed.ac.uk
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nonlinear effects. These nonlinear effects will be generalised via correction terms discovered by machine learning from a large numerical simulated dataset. This dataset also allows for extending the theory
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modelling tools, depending on your profile, to unlock – and inform the design of – disruptive solar technologies. You will be expected to undertake some project management activities, supervise multi
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spectroscopy and HPLC), organic synthesis, electrochemistry, hydrogel soft matter and modelling. You will be mentored by Dr. Maguire and will learn how to design and manage projects, how to conduct research, how
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Supervisory Team: Prof Neil Sandham PhD Supervisor: Neil Sandham Project description: This project is focused on scale-resolving simulations (large-eddy and direct numerical simulation) combined
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Cranfield University and Magdrive will study plume effects of Magdrive's dynamic pulsed plasma thruster on relevant targets. Simulation of plasma expansion and condensation in the space environment will be
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. The enhanced image quality will support earlier and more reliable detection of eye diseases. Combining artificial intelligence with mathematical modelling, this non-invasive, cost-effective approach has
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will lead the development of novel motor topologies optimised for this cutting-edge material. Supported by experienced supervisors, the student will be able to design, model, and validate working
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information from high-quality videos that share content with distorted footage as constraints in the learning process of modelling algorithms. This method uses the characteristics and knowledge embedded in high