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Modeling naturally fractured reservoirs is re-gaining interest in the Oil & Gas industry and academia for application in carbonate fractured reservoirs and unconventional reservoirs where natural
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, electrical and optical characterizations. This position requires conducting translational research in next-generation large-area nanofiber acoustic sensor platforms in structural health monitoring applications
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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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The lab of professor Jesper Tegnér at KAUST has openings for three postdoctoral fellowships in Data-driven Machine Learning for unbiased Discovery of Generative Models with special reference
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themes: (a) learning efficiency, computational creativity (zero, few-shot, and long-tail learning of 2D and 3D vision tasks. This also includes efficient generative models that are capable of generating
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Postdoctoral Fellows have access to KAUST’s exceptional research infrastructure, including one of the world’s fastest supercomputers, a full suite of advanced imaging facilities, a class 100 cleanroom for
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to KAUST’s exceptional research infrastructure, including one of the world’s fastest supercomputers, a full suite of advanced imaging facilities, a class 100 cleanroom for nanofabrication, a seires of research
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improvement. Project Our group has recently advanced our understanding of bread wheat domestication by analyzing genomic data from wild wheat relatives (https://www.nature.com/articles/s41586-023-06389-7
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feasibility studies of CCS using mechanistic modeling and simulation including uncertainty analysis and risk assessment. Applications are sought for a 1-to-2-year postdoctoral fellow position. The position
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depends on the background of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep learning using 3D data. More