21 scholarship-vacancy-for-phd-in-computational-physics Postdoctoral positions at King Abdullah University of Science and Technology
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The Division of Physical Science and Engineering at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, invites applications for Postdoctoral fellow in Mechanical Engineering
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To apply for this position, please send an email to Nouf and ensure that you include the following documents (combined in a single pdf file): Cover letter Curriculum vitae Contact information for three references About KAUST: King Abdullah University of Science and Technology (KAUST) is an...
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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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of mineral resources in Saudi Arabia by developing innovative approaches to mineral exploration, mining, and mineral processing. The working group will initially consist of 1 PhD student and 2 MSc students
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to the development of mineral resources in Saudi Arabia by developing innovative approaches to mineral exploration, mining, and mineral processing. The working group will initially consist of 1 PhD student and 2 MSc
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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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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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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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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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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