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experience of power electronics converter topologies and power semiconductor devices which are applicable for low voltage and high voltage power converter systems. Strong technical knowledge of gate driver
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to work on a project to conduct the research on development of low-frequency metamaterials for wireless power transfer. Key Responsibilities: To conduct research in power electronics for wireless power
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A Research Fellow position is currently available in the School of Electrical & Electronic Engineering. The Research Fellow will work on a project to conduct the research on development ingestible
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on the development of security and privacy enhanced solutions for AI accelerators. Job Requirements: PhD’s degree in Computer Engineering, Computer Science, Electronics Engineering or equivalent. Strong background in
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system flexibility Modelling of DER-based integrated grid ancillary services that maintain reliability and stability Job Requirements: Ph.D. in Electrical/Computer Engineering specialized in Power Systems
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Electronic Engineering or related field 1-year research experience in related area Expertise in Electromagnetic Simulation Expertise in Wireless Power Transfer Expertise in Power Electronics Publication track
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Intelligence (AI) and Machine Learning (ML) algorithm and 3D SLAM for automotive robot navigation etc. Job Requirements: A Ph.D degree in Electrical & Electronics Engineering or Computer Engineering. Relevant
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undertake research in computer vision, NLP, and machine learning To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community
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, focusing on loss and thermal analysis. Experimental testing for high-power motor system, focusing on loss and thermal analysis. Job requirements: PhD in Electrical and Electronic Engineering or related field
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satisfactory performance. Successful candidates will be involved in a project that is related to generative design. Key Responsibilities: To independently undertake research in computer vision and deep learning