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Field
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/PhD) in their research activities, where appropriate. They will be responsible for maintaining accurate and complete physical and electronic records of their work and should be prepared to assist with
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UK honours degree or equivalent in Engineering, Chemistry, Applied Physics, or a related discipline; a Master’s degree in these subjects would be of advantage. Funding This is a Fully-funded
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of real-time digital twin (physical or Artificial Intelligent based) of electric propulsion system including propulsion motors, power converters, fuel cell and batteries etc within the real-time simulation
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all of the topics listed above. Informal enquiries related to the position should be directed to Prof Ben Glocker: b.glocker@imperial.ac.uk For queries regarding the application process contact Jamie
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supervisors spans five departments at University of Nottingham including Architecture and Built Environment, Electrical and Electronic Engineering, Mathematics, Physics and Social Sciences. The PhD programme
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their interest should be sent to: m.watts@salford.ac.uk Note to applicant: In addition to applying for this role the successful candidate will also be required to complete the University application process which
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Embark on a ground-breaking PhD project harnessing the power of Myopic Mean Field Games (MFG) and Multi-Agent Reinforced Learning (MARL) to delve into the dynamic world of evolving cyber-physical
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the formation of biofilms and the development of processes to formulate / process them into new health/consumer care products e.g. oral/skin health products. The project will focus upon extending UoN patented
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://hr.admin.ox.ac.uk/staff-benefits Application Process Applications for this vacancy are to be made online. You will be required to upload a Supporting Statement and CV as part of your online application. Either using
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functional performance of the components and the key process parameters. The project will deal with the design of special process setups, testing its working principles and performances followed by