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the electrical and electronic engineering industry and preferably is familiar with smart electrical power grids. Prior knowledge on solar photovoltaic and energy storage systems would be an advantage. Experience
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under real-world conditions to verify system operation against targets and demonstrate the reliability of the technology for use in backup power, grid stabilisation, and renewable energy integration
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and develop machine learning and mathematical optimization solutions for electric vehicle (EV) fleet charging scheduling problems with considerations of various smart power grids, battery degradation
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stability assessments and control development. You will: contribute to delivering the CfNETR project(s) in smart power system engineering; develop literature reviews and maintain data and knowledge
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Fellow in power systems to conduct research on energy management, electricity markets, renewable energy, smart grids and microgrids. The Research Associate/Research Fellow is also expected to support
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equivalent from a recognized University. Minimum 1 year of relevant experience in the electrical and electronic engineering industry and preferably is familiar with smart electrical power grids. Prior
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno
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Are you a researcher looking for your first challenge? Do you have a background in smart grid operation and control? Do you want to further your career in one of the UK’s leading research-intensive
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equivalent from a recognized University. Minimum 1 year of relevant experience in the electrical and electronic engineering industry and preferably is familiar with smart electrical power grids. Prior
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grid. To explore the post further or for any queries you may have, please contact: Professor Kang Li , Chair in Smart Energy Systems Tel: +44 (0)113 343 2045 Email: K.Li1@leeds.ac.uk Please note that