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Education: Ph.D. or M.S. in Computer Science, AI, Computer Vision, or related field Experience: 3+ years in computer vision and deep learning, with specific focus on microscopic imaging, generation
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-disciplinary expertise and activities in the following domain: Computational methods for bioengineering Topics of focus include (but are not limited to): Automation and robotics Genomics Biological imaging
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: The candidate should have expertise in machine learning and computational methods applied to seismic imaging, inversion, earthquake monitoring, or subsurface characterization. The candidate should have expertise
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The Statistics (STAT) program in the Computer, Electrical, and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa) at King Abdullah University of Science and Technology
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, SHS, moisture absorbing polymers, etc.) and varying fertilizer and irrigation regimes. Experience in statistical methods is a huge plus. Ability to quickly test hypotheses via pot-scale studies
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varying fertilizer and irrigation regimes. Experience in statistical methods is a huge plus. Ability to quickly test hypotheses via pot-scale studies (greenhouse and/or laboratory) and implement in
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The Applied Mathematics and Computational Sciences (AMCS) program in the Computer, Electrical and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa ) at King Abdullah
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The VCC center at KAUST is looking for research scientists in Prof. Wonka's research group. The topics of research are computer vision, computer graphics, and deep learning. A suitable candidate
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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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experience with molecular and cell biological methods. The applicant will work to advance our knowledge of viral vector production in versatility, stability and efficacy with modern techniques from plasmids