8 learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" "Fields Institute" Fellowship positions at King Abdullah University of Science and Technology
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 15 hours ago
Continual Language Learning , ( ICLR ’20), Yuanpeng Li, Liang Zhao, Ken Church, Mohamed Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 15 hours ago
learning using 3D data. More information about the research group and KAUST can be found under the following links: http://peterwonka.net/ https://cemse.kaust.edu.sa/vcc https://www.kaust.edu.sa/en If you
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 15 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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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 15 hours ago
your own scientific pursuits and passions. We offer a highly competitive salary , free housing and subsidized medical insurance. For more information about living and working at KAUST, please visit https
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postdoctoral researcher for a 2-year position (extension possible) in a project on exploration for Red Sea hydrothermal vent fields. The Red Sea Rift hosts some of the world's largest known submarine
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 15 hours ago
+ nationalities) Qualifications Core Requirements PhD in Computer Vision, Medical Imaging, Applied Machine Learning, or a closely related field. Hands-on experience with generative models — diffusion (DDPM/LDM
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 15 hours ago
) under the mentorship of Prof. Jürgen Schmidhuber. This project, located at the intersection of Reinforcement Learning and Material Science, focuses on developing innovative solutions for the discovery
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opportunities for social, sporting, and learning activities outside of work. Qualifications Basic Qualifications PhD in Earth Sciences, Geosciences, Geochemistry, Mineralogy or a closely related relevant field