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project include two aspects: (1) based on the cutting-edge technologies from deep learning, computer vision or physics-informed machine learning, develop robust surrogate forward models to predict
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be involved in the three-year project “High Dimensional Hierarchical Optimization methods for Machine Learning and Stochastic Optimal Control”. Background or expertise in one or more of the following
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https
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learning. A suitable candidate should have publications in good venues, mainly CVPR, ICCV, ECCV, ICLR, NeurIPS, Siggraph, and Siggraph Asia. Various research topics are available and the exact research topic
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, living and working on campus, with many opportunities for social, sporting, and learning activities outside of work.
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, with many opportunities for social, sporting, and learning activities outside of work.
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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coarse grained reconfigurable arrays (CGRAs), virtualisation of FPGAs using partial reconfiguration, and accelerator support for machine learning. Postdocs at KAUST enjoy generous salaries and free
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. These workflows will then be applied in relevant Saudi Arabian contexts to help discover new ore deposits. The position will combine techniques from geological modelling, geostatistics, machine learning, and
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, an annual travel allowance, 30 paid vacation days, and other generous benefits. KAUST is a vibrant and international community, with many opportunities for social, sporting, and learning activities outside