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conventional simulators. Finite element-based methods such as Mixed-Finite-Element or Control-Volume methods are convenient thanks to their suitability for complex unstructured grids. Applications are sought
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We seek a postdoctoral associate with PhD degree in Physics, Electrical Engineering, Materials Science or in related fields specialized in acoustic sensors, device fabrication, and electromechanical
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Elhoseiny, Code: https://github.com/yli1/CLCL Uncertainty-guided Continual Learning with Bayesian Neural Networks (ICLR’20), Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, Marcus Rohrbach, Code: https
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) learning numerical methods for wave-equation-based processing, imaging, and inversion. Wave phenomena are ubiquitous in science, and they extend to objectives ranging from global Earth discovery, to natural
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, free housing and subsidized medical insurance. For more information about living and working at KAUST, please visit https://www.kaust.edu.sa/en/live If you are enthusiastic about working at the forefront
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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 are interested in joining us