26 distributed-systems-networks-phd Postdoctoral positions at King Abdullah University of Science and Technology
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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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· PhD in Materials science, chemistry, physics, polymer science, or related field · Strong background in ferroelectrets, piezoelectric materials, voided charged polymers or piezocomposites
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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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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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-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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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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for three references About KAUST: King Abdullah University of Science and Technology (KAUST) is an international graduate-level, merit-based research university dedicated to advancing scientific and
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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