14 condition-monitoring-machine-learning Postdoctoral positions at King Abdullah University of Science and Technology in Saudi Arabia
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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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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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are looking for young scientists who are passionate about water desalination and machine learning with its potentially transformative applications in research and industry. The two-year post-doctoral position
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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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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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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
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on well-identified frames), validated models in operational conditions (New models based on real in-situ observations and mechanism). Microstructure manipulation for tailoring macroscopic response: Toughing
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on well-identified frames), validated models in operational conditions (New models based on real in-situ observations and mechanism). Microstructure manipulation for tailoring macroscopic response: Toughing
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types of mineral deposits, it is probably the country with the most exciting mineral exploration opportunities right now. Conditions and life at KAUST Applications are sought for a two-year Postdoc
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platform in the field of testing composite materials for in-situ testing in conditions relevant to the energy sector (high pressure, high temperature, extreme environments). Participate in the generation