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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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, perform simulation studies, and apply developed methods to empirical datasets. The positions do not involve any lab work. The work includes mathematical modeling, algorithm development, statistical analysis
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Responsibilities: Design and implement advanced AI/ML models for healthcare applications, including predictive analytics and generative AI solutions. Develop and validate digital phenotyping algorithms using
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analysis; (b) develop and implement algorithms for 3D perception (e.g. segmentation, localization and mapping); (c) design and execute experiments to evaluate, validate and refine algorithms and
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, particularly Python; (ii) use of parameter optimization algorithms, particularly PEST and PEST++; (iii) remote sensing applied to the water cycle; and (iv) application of machine learning techniques to spatio
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scholarship holder will contribute to several research activities, including: - Design and implementation of event-based data compression algorithms, including lossy and learning-based approaches. - Development
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research project/s under the guidance of the grant CIs (Prof Francis, Prof Tanaka, and Dr Hendriksen), and contribute to development of research activities. Support the dissemination of research outcomes
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pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute for Experiential AI is built around the
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research into the nature of mathematical understanding, including, depending on their interests, conducting psychological experiments, developing novel mathematics, inventing new algorithms, and making new
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pioneering research and innovation hub in AI—one that will shape the way humans and machines collaborate for decades to come. Led by Prof. Usama Fayyad, the Institute for Experiential AI is built around the