54 algorithm-development-"Multiple"-"Simons-Foundation"-"Prof" "UNIS" positions at King Abdullah University of Science and Technology in Saudi Arabia
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on the development of new methods integrating a variety of data types (remote sensing, geology, geophysics, geochemistry) for geological modelling and advanced exploration targeting of mineral deposits
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King Abdullah University of Sciences and Technology (KAUST) invites applications for a faculty position in Emerging Semiconductor Materials and Devices. We are particularly interested in candidates with experience in areas such as flexible and large area electronics, neuromorphics, energy...
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highly competitive candidates eager to pursue innovative research addressing fundamental questions and developing cutting–edge technologies for application in marine systems. This position offers a unique
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, merit-based research university dedicated to advancing scientific and technological education and research, acting as a catalyst for innovation, economic development and social prosperity in the region
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technological education and research, acting as a catalyst for innovation, economic development, and social prosperity in the region and the world. Based near Jeddah, Saudi Arabia, KAUST has attracted top-notch
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competitive candidates eager to pursue innovative research addressing fundamental questions and developing cutting–edge technologies for application in marine systems. We are especially interested in
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molecular biology to address critical questions in genome biology, evolution, and disease resistance of wheat. Our mission is to perform impactful, curiosity-driven research that translates into crop
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The Machine Learning (ML) group led by Professor Ricardo Henao at KAUST (King Abdullah University of Science and Technology) has multiple openings for Postdoctoral level positions to conduct
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We are seeking motivated researchers with expertise in large-area 2D materials growth for sensor and transistor applications. The focus is on developing wafer-scale 2D materials using CVD, PLD
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is to develop a modeling framework including the use of Random-Walk method to predict NMR measurements, pore-scale finite-element modeling on 3D digital models, generated from CT-images to predict