57 phd-in-computer-vision positions at King Abdullah University of Science and Technology
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Application documents: Brief cover letter, explaining your motivation for applying, Detailed curriculum vitae (including your email address), Complete transcript of grades from all your university-level studies. We do not ask for more information/documents at this point (but you can provide more...
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The Program Manager, Community Development is responsible for leading the planning, development, and execution of strategic community programs, initiatives, partnerships, and engagement activities
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The Computer Vision-Core Artificial Intelligence Research (Vision-CAIR ) group led by Prof. Mohamed Elhoseiny at the CS Program of the King Abdullah University of Science and Technology (KAUST) is
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The Electrical and Computer Engineering (ECE) Program within the Computer, Electrical, and Mathematical Sciences and Engineering (CEMSE) Division at King Abdullah University of Science and
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the world’s pressing scientific and technological challenges, broadly aligned with the objectives of Saudi Arabia’s VISION 2030. All relevant research areas of Computer Science will be considered, with a
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to addressing the world’s pressing scientific and technological challenges, broadly aligned with the objectives of Saudi Arabia’s VISION 2030. All relevant research areas of Computer Science will be considered
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The Applied Mathematics and Computational Sciences (AMCS) program in the Computer, Electrical and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa) at King Abdullah
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The VCC center at KAUST is looking for postdoctoral researchers and research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep
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We invite applications for a faculty position in computational science and engineering with a focus on geophysics or fluid dynamics, as well as machine learning with one of the following experiences
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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