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platform. Training the development digital-twin using real-time data from hardware available Electrical power level studies with developed digital twin to identify visible solutions for distribution electric
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. This project seeks to advance energy autonomy by optimising power conversion, storage, and distribution in such systems, enabling broader adoption in real-world applications. The project aims to develop a PMC
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for distribution electric propulsion. Who we are looking for We are looking for enthusiastic, self-motivated applicants with first-class degree in Electrical Engineering, Aerospace Engineering or Computer Science
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: The occurrence and distribution of species within and around solar parks, identifying key “winners and losers” in terms of biodiversity. How species interactions, including plant-pollinator networks
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the feasibility of using federated learning or distributed learning approaches to build and update device profiles without sharing raw traffic data. Furthermore, the system's ability to adapt to legitimate changes
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Sustainability Post-COVID-19 Project Supervisors: Professor Rebecca Randell, Dr Joshua Pink Project Description: The COVID-19 pandemic accelerated the drive to home working and acceptance of the distributed
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challenges to the electricity transmission and distribution system, as solar power is not dispatchable and therefore its incorporation as a major element of the generation mix requires the accurate prediction
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and social acceptance. This research will develop an efficient variable renewable energy (wind and solar) input system architecture to produce, store, and distribute variable power output (electrical
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alloying elements from the OBMs like V and Mn (which depends on the iron ore sources) will be distributed between the steel, slag and dust during EAF steelmaking. The presence of these residual elements in
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, particularly in computer networks, operating systems, computer architecture and distributed systems Excellent programming, system building and measurement skills are required Be familiar with, and ideally worked