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                Applicants must have a PhD in Computer Engineering, Computer Science, or Electrical and Computer Engineering, and have published their research in prestigious conferences and journals in related 
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                One postdoctoral position is currently available at King Abdullah University of Science and Technology (KAUST) for a collaborative project with a starting date of April 1, 2020. The candidate will 
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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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                , but is projected to grow to 2 postdocs (incl. this positions), 3 PhD students, and a variable number of MSc students. KAUST provides a highly collaborative research environment, and active engagement 
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                students, but is projected to grow to 2 postdocs (incl. this positions), 3 PhD students, and a variable number of MSc students. In addition, KAUST provides a highly collaborative research environment, and 
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                across a wide range of diverse and cutting-edge fields. Opportunities exist within our well-funded research areas such as AI, Intelligent Secure Systems, Intelligent Manufacturing and Robotics 
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                -class students, faculty, and researchers from over 100 nationalities. The result is a network of talent that enables radically dierent perspectives. With holistic support for creative minds and unmatched 
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                holding a PhD in chemical, environmental or process engineering, to apply for a full-time post-doctoral fellowship position in the field of water desalination, focusing on the development of an artificial 
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                This postdoc position is for a specialist in the fabrication of silicon heterojunction solar cells to be integrated into monolithic silicon perovskite tandem solar cells. For this position, we 
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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