9 deep-learning-phd Postdoctoral positions at King Abdullah University of Science and Technology in Saudi Arabia
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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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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
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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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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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. 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
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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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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 state-of-the-art bioinformatics pipelines; (ii) single-cell analysis, multi-omic analysis; (iii) spatial transcriptomics bioinformatic analysis. Learning and implementing Systems Medicine-based analysis