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Control” (DP250101137). The Postdoctoral Research Fellow is expected to undertake research on control theory and machine learning techniques for project DP250101137. The Postdoctoral Research Fellow will
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control technologies—particularly model predictive control—can be integrated with established low-carbon heating systems like heat pumps. These technologies aim to address both grid-level and end-user
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automation in food manufacturing - smart sensors, digital twins, and AI-driven food quality control and processing; Food safety - supply chain tracking/monitoring, blockchain Biotechnology: Host strain
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fellow to support the works on Emission Control of Ammonia Combustion. The job scope of the manpower is to conduct combustion experiments in constant volume combustion chamber; establish experimental
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fellow to support the works on Emission Control of Ammonia Combustion. The job scope of the manpower is to conduct combustion experiments in constant volume combustion chamber; establish experimental
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attacks on QKD sources or single-photon detectors. Experience with microelectronics, fast signal processing, and circuit design, including FPGA-based control, real-time acquisition, and hardware description
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fellow to support the works on Emission Control of Ammonia Combustion. The job scope of the manpower is to conduct combustion experiments in constant volume combustion chamber; establish experimental
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management system for the e-vessel microgrid for coordinated control of multiple energy sources considering cost, carbon, and operation constraints. Operate the simulated electrical model on a real-time system
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-time PAT data streams to enable predictive monitoring, dynamic process adjustments, and improved control strategies. Working closely with AstraZeneca, the postholder will apply these digital twins and
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. These models will incorporate real-time PAT data streams to enable predictiv e monitoring, dynamic process adjustments, and improved control strategies. Working closely with AstraZeneca, the postholder will