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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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/physics/biology) or engineering. The ideal candidate should have some understanding in the areas of Materials Science, Chemistry, Physics, Metallurgy, or Mechanical Engineering. The candidate should be self
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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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for UK or EU students, and £27,720/year for overseas students) and the living expenses (approximately £800-£1000 per month). The Centre for Materials at Cranfield will cover the costs associated with
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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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technologies. Liquid hydrogen (LH2) is a promising technology for decarbonizing civil aviation, offering zero in-flight CO2 emissions. Its high energy density per unit mass, about three times higher than
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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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encouraged. For further information about application please visit Applying for a research degree .