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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 19 hours ago
cutting-edge machine (deep) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from
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MOF synthesis and characterization. Special consideration will be made to candidates with experience in automation or machine learning. The postdoc will join a group which is focused on pioneering
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Scientific Machine Learning Postdoctoral Scholar Application- 2026 Join Rebecca Willett's research group advancing scientific machine learning, with applications to climate science, astronomy, and
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 19 hours ago
areas: computer vision, computer graphics, and deep learning. We require documented experience about computer vision, machine learning, deep learning or optimization, demonstrated by high-quality
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 19 hours ago
Technology (KAUST) is looking for postdoctoral researchers in the area of computer vision, AI, and machine learning. The initial appointment will be for 2 years with a possible extension with a
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learning techniques in multiple modalities of medical imaging (e.g. fundoscopy images, OCT scans, MRI, CT, X-ray and digital pathology). We bridge the gap between machine learning research and clinical
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- Epigenomics, Machine Learning & 3D Genome Biology Employer NYU Langone Health, Skok Lab Location New York City, New York (US) Salary Postdoc: $70,000+ annually, plus benefits; Senior Computational Biologist
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, numerical method, and data-driven/machine-learning approaches, including: · Numerical simulation of kinetic equations: fast algorithms with stability/convergence analysis; · Data-driven and machine
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University of California, San Diego | Estancia de San Diego, Guanajuato | Mexico | about 5 hours ago
the topic of machine learning-based ocean state estimation to begin in Spring/Summer 2026. The successful applicant will develop and implement data-driven tools, underpinned by scientific machine
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theoretical background with evidence of both skills related to convex optimization, machine learning, stochastic gradient descent, and deep learning Demonstrated experience in developing, analyzing, and