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TU Berlin seeks candidates for a PostDoc position in the field of stochastic analysis, in particular, stochastic PDEs, mathematics of machine learning, and stochastic dynamics. Our offer * PostDoc
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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 16 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 16 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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King Abdullah University of Science and Technology | Saudi Arabia, | Saudi Arabia | about 16 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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informatics, or related field. • Strong knowledge and experience in natural language processing, machine learning, and deep learning. • Strong written and oral communication skills in English. • Ability to
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. The project is conducted in collaboration with the deep probabilistic programming group of Thomas Hamelryck : https://di.ku.dk/english/research/groups/machine-learning-in-biology/?pure=en/persons
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machine learning within the scope of ACAG. The postdoc will have various opportunities for professional development, including contributing to and leading grant proposal development (e.g., external
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performance utilizing a variety of tools including life-cycle assessment (LCA), machine learning techniques, and/or optimization methods. This position will carry out state of the art research into the
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N2O from wetlands. We envisage combining process-based modelling and machine learning, as well as integration of Earth observation data into the modelling framework. The objective is to quantify the
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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