9 computer-networking research jobs at King Abdullah University of Science and Technology
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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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Elgammal, Bingchen Liu, Mohamed Elhoseiny, and Marian Mazzone, CAN: Creative Adversarial Networks, International Conference on Computational Creativity(ICCC), 2017 Theme B continual learning (selected papers
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of bioinformaticians, computer scientists, biotechnologists, biologists, and biochemists. The successful candidate will also enjoy an environment aimed to facilitate progress in the research career: networking, student
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topics. Candidates should have some experience working with FPGAs as well as an understanding of computer networks. Experience with both RTL and HLS design is favoured. The ideal candidate would have some
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genomics, protein engineering, cloning/assembly workflows, cell line development). You will work closely with computational experts to establish innovative, high-throughput, high-fidelity screening platforms
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fractures can play a key role on production performance. One of the persisting challenges is to create complex 3D fracture networks and solve multiphase flow efficiently. None of the existing tools can
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areas will be considered when selecting candidates: Machine Learning, Neural Networks, Numerical solutions of Partial Differential Equations and Stochastic Differential Equations, Numerical Optimization
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We invite applications for multiple Postdoc positions in the Accelerated Connected Computing Lab (ACCL) at KAUST! The new research group, supervised by Suhaib Fahmy explores hardware acceleration
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research in the field of machine learning, more specifically, deep learning and representation learning architectures. Application areas of ML include, but are not limited to, computer vision, natural