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in simulation, prediction, and analysis of large-scale and complex fluid systems. Special emphasis will be directed toward incorporating high-performance computing, advanced algorithms, machine
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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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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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advice and assistance to faculty on sources of funding and the requirements of sponsors and develop individual search strategies for funding; Identify and distribute funding opportunities for KAUST faculty
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assistance to faculty on sources of funding and the requirements of sponsors and develop individual search strategies for funding; Identify and distribute funding opportunities for KAUST faculty; In liaison
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are in particular targeting development of data-driven high-performance computing techniques for unbiased discovery of generative models & theory and algorithms for network inference with special reference
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technology that can be applied while drilling within the wellbore to provide various spatially continuous measurements, such as formation porosity, permeability, water, and hydrocarbon distributions
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for data streams from oceanographic autonomous vehicles, remote sensor sites, and various other instrumentation into the database. Develop interfaces to distribute scientific data sets to adjoining systems