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Field
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industry partners. Design, implement, and validate advanced reinforcement learning models. Utilize reinforcement learning and evolutionary algorithms to discover new chemical materials. Publish and present
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team to develop integrated control algorithms for autonomous cubesatellite formation flying. The controllers that will be developed during this project will differ from previous work on this topic by
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algorithmic advances and aim at publishing them at these top venues. More details about the position can be found here. As a KAUST postdoc or researcher, you will have access to state-of-the-art research
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learning or deep learning research project; (b) evaluate the proposed algorithms; and (c) conduct a real-case analysis. Qualifications For the Research Fellow post, applicants should have a doctoral
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-photonic computing architectures; Silicon-photonic network architectures Machine Learning Algorithms/Systems: Experience in design and use of ML algorithms; Experience in using ML for designing computing
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Engineering or equivalent from a recognized University. Major in Power Engineering will be advantageous. Minimum 5 years of relevant experience in power electronics, drives, control algorithms, optimization
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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domainspecific knowledge with data
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to shape the renewable energy management system by developing novel real-time control & optimization algorithms. Pilot demonstrations on partner radio telescope facilities such as APEX and the Sardinia Radio
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analyses in nonclinical drug development. The postdoctoral role involves designing and implementing algorithms for anomaly detection, segmentation, and classification to contribute to the development
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, or a related field of thermal nanophotonics. Excellent publication records will be preferred. Experience in matlab, MEEP, RCWA and other softwares and algorithms. Excellent publication track records