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community. We are now looking for a Doctoral Researcher in AI and Quantum-Inspired Optimization for Sustainable Energy Systems Are you passionate about developing AI-based and quantum-inspired solutions
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of the elderly to space robotics. We are now looking for a postdoctoral researcher in quantum algorithms and optimization for Life Science applications. Are you as excited about quantum technology and its future
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developing learning-based perceptive approaches. You will develop learning and/or optimization based approaches to multi-robot path and motion planning and coordination, integrating multi-modal perception and
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world
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pathogens in the hospital environment, spanning all aspects from sampling to sequencing to bioinformatics analysis. This should include experience in developing and optimizing laboratory protocols
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key role in driving high-impact research, developing innovative objectives, and formulating proposals within cutting-edge fields, including Computer Vision, Digital Healthcare, AI Optimization, and
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manufacturers lose between 2% and 5% of output through scrap and rework, driving unnecessary material consumption, machine hours, and energy use. The Lean Optimal feasibility study will investigate whether a
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deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical optimality with computational efficiency. Reinforcement Learning through Stochastic Control. We will
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nanostructures and device optimization using simulations. The goal is to develop precise control of specific emission properties such as polarization, color, and angular distribution while simultaneously
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plant-colonising bacteria and integrate them into the chromosomes of appropriate bacterial chassis. Control systems will be designed to restrict expression to target plants and ensure optimal expression