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collaboration with IHL and an industry partner. where you will be part of the research team to develop and demonstrate Building-to-Grid Integration through Intelligent Optimization and Predictive Control at SIT’s
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that are relevant to industry demands while working on research projects in SIT. We are seeking a talented Power Electronics Engineer or Research Fellow to design and optimize high-frequency magnetic components and
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control strategies for optimizing wind farm performance and reliability. Additionally, the role includes documenting findings in formal reports and contributing to the development of high-quality journal
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performance and yield; spanning from optimal “device recipe” prediction to automated testing and yield assessment. The post-holder will have the ability to engage with world-leading experts across AI and
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control strategies for optimizing wind farm performance and reliability. Additionally, the role includes documenting findings in formal reports and contributing to the development of high-quality journal
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include the analysis of VOCs emitted from plants to understand optimal conditions for controlled environment agriculture (CEA). By tailoring ‘light recipes’, CEA can optimise plant growth, enhance
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screening and engineering for microbial bioprocess development; microbial physiology and adaptation for industrial applications; high-throughput screening and automation for strain optimization
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calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to Level 4 Spine Point 28 - 30
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and experience in using these algorithm for electrical engineering problems Excellent knowledge on control and optimization algorithms with implementation to power electronics design experience Good
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This is a Research Fellow post to support the NIHR funded programmes OPtimal Timing of Induction of labour to improve Maternal and perinatAL outcomes (OPTIMAL): An individual participant data meta