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triboelectric nanogenerator (TENG) to sustainably power ingestible medical devices. The aim is to harness mechanical energy from natural intestinal peristalsis to enable battery-free operation of autonomous
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
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science, e.g, by leading to more effective batteries. The Research Assistant/Associate will join the Machine Learning Group at the Department of Engineering, working with Prof. José Miguel Hernández Lobato
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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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, both as an intrinsic scientific curiosity and in order to be able to propose new designs for quantum devices (quantum batteries, quantum engines and so on). Therefore, the results from this project
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SpeedGoat. Development 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
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, material synthesis, catalysis, analysis and characterisation, battery cell, recycling, sustainability and life cycle analysis. Theory and Modelling Theoretical work is conducted on very different length- and
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the operational life of battery-powered devices and reducing the environmental impact of large-scale deployments. Advancements in this area support the development of sustainable technologies across various
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– both CO2 and non-CO2 (including contrails) – of various technologies, including electric aircraft (battery- and fuel cell-powered), hybrid-electric aircraft, next-generation propulsion systems
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loads — EV fleets, residential batteries, smart heat pumps, and data-center clusters — across distribution and transmission networks is critical to unlocking deep decarbonization and maintaining grid