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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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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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information about the research group and KAUST can be found under the following links: http://peterwonka.net/ https://cemse.kaust.edu.sa/vcc https://www.kaust.edu.sa/en If you are interested in joining us
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. Develop sensing principles, data acquisition, and measurement systems. Upscale technology and validate its integration into a variety of structures, including structures for mobility, energy, and civil
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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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, the generated data can be used to optimize mineral extraction processes from existing mines within a geometallurgical framework. The position will mostly focus on the development of measurement protocols and data
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and research infrastructure with the possibility to receive training on diverse instruments by experts in their fields. Skill diversification, e.g. programming courses in AI/ML and data visualization
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We use cookies which are necessary to make our site work. We may also use additional cookies to analyse, improve and personalise our content and your digital experience. For more information, see
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boasts world-class equipment, research and recreational facilities, and computational resources. It is the leading university in citation per faculty according to the QS Rankings. Further information can