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electronic engineering and/or applied mathematics, in particular, in one or more areas of learning, control and optimisation of multiagent systems. Experiences in dealing with complex networks and/or variable
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electrical and electronic engineering and/or applied mathematics, in particular, in one or more areas of learning, control and optimisation of multiagent systems. Experiences in dealing with complex networks
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electrical and electronic engineering and/or applied mathematics, in particular, in one or more areas of learning, control and optimisation of multiagent systems. Experiences in dealing with complex networks
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developing the next generation of smart wind turbine blades. You will play a key role and have skillset in one or more areas of electrical engineering, including power electronics, inverter control, rotating
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, evaluating and integrating emerging weed control technologies for Australian broadacre cropping systems. Whether you are an emerging researcher or an experienced postdoctoral scientist, this is an opportunity
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of artificial intelligence and advanced hardware systems? An exciting opportunity has arisen to join the newly created Silicon Platforms Lab (SiP Lab) within the School of Engineering at Macquarie University
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mechanisms of adaptive and acquired drug resistance, exploring network-level control and feedback in cell signaling systems, identifying novel drug targets and therapeutic strategies, and developing predictive
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found here: https://www.gov.uk/guidance/academic-technology-approval-scheme . Informal enquiries: Prof James Gates gates@southampton.ac.uk As a university we aim to create an environment where everyone
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control systems. You will work collaboratively with a multidisciplinary team to advance renewable energy technology through cutting-edge simulation, experimental validation, and system integration. We
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, electrical systems, or intelligent control systems. You will work collaboratively with a multidisciplinary team to advance renewable energy technology through cutting-edge simulation, experimental validation