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numberSATM533 Entry requirements Applicants must have a B.Sc. in electronic / information engineering or computer science and must either have or close to having a Master’s degree (must be completed by the time
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analytical frameworks grounded in Mean Field Game (MFG) theory and Multi-Agent Reinforcement Learning (MARL), which are tailored for eCPS. These frameworks will facilitate the creation of effective control
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gas turbine sensor data, if available, will be utilized to validate the developed digital twin in order to estimate non-measurable health parameters of major gas path components, including compressors
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zone in a very complex manner and lead the modelling to an imperfect zone of assumptions. These complexities allow the researchers to use approximations for useful lifetime calculations. Based
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mandatory. Funding Self-funded. The student needs to support the PhD tuition fees (£5,006/year for UK or EU students, and £27,720/year for overseas students) and the living expenses (approximately £800-£1000
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mandatory. Funding Self-funded. The student needs to support the PhD tuition fees (£5,006/year for UK or EU students, and £27,720/year for overseas students) and the living expenses (approximately £800-£1000
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land availability for nature-based solutions around SO; assessing expected SO contaminant loads; quantifying pollution, water volume attenuation and co-benefits provided by different nature-based
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treatment. It is essential for candidates to hold a driving licence (incl. an international licence) as the role involves some field sampling around the UK. The candidate should be self-motivated, have good
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training programme in respect of industry-specific skills, and access to hotfire facilities at Westcott, Machrihanish, and elsewhere. You can learn more about the programme at r2t2.org.uk. Kick stages are a
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opportunities to access some of the MSc courses and CPD short courses relevant to the research and attend and publish papers in international conferences. Cranfield operates a substantial Doctoral Researchers