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innovative, technology-driven research in Infection Biology, Microbiomics, and Epidemiological Disease Modelling. Preference will be given to those with expertise and a proven track record in one
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seeking to expand research, higher education and innovations in the field of Marine Data Modelling and Integration. Applications for a faculty position at the rank of: Assistant Professor are invited from
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-inspired approaches for modeling, designing, and predicting the response of composite systems. Responsibilities: Develop AI approaches for predictive multi-physics response of composites in Energy
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containment. The prohibitively high computational cost of such simulations necessitates the development of efficient and robust surrogate models for general GCS modeling tasks, especially when inverse modeling
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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
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Modeling naturally fractured reservoirs is re-gaining interest in the Oil & Gas industry and academia for application in carbonate fractured reservoirs and unconventional reservoirs where natural
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: Docker, MLflow ○ Expertise in 2D/3D image segmentation, detection, and Stable Diffusion techniques (U-Net, V-Net, DeepLab) ○ Strong experience with Generative AI models (GANs, VAEs
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The lab of professor Jesper Tegnér at KAUST has openings for three postdoctoral fellowships in Data-driven Machine Learning for unbiased Discovery of Generative Models with special reference
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devices Design intuitive interfaces for AI model interaction and advanced image analysis Manage high-performance databases optimized for large-scale imaging datasets Implement security measures including
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Science and Engineering Division. The Composites Lab started at KAUST in 2009 and is an integrated environment for composite science, combining modeling and experimental expertise in a single working