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to data-driven (machine-learned) representations. In particular, we are interested in the joint applicability of such models and to what extent simpler models (possibly based on machine learning) can be
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-performance computing, via reduced-order models to data-driven (machine-learned) representations. In particular, we are interested in the joint applicability of such models and to what extent simpler models
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(BEM) is an advantage. Experience with either scientific computing or numerical optimization is an advantage. Experience with unsupervised machine learning is also an advantage. Applicants must be able
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machine learning is a requirement. Experience with programming and app development will be emphasized. Personal skills, including independence, abilities to cooperate, a great work capacity and enthusiasm
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(for instance mathematics, statistics, medicine with a strong emphasis on computational and programming aspects). Experience in machine learning is a requirement. Experience with programming and app development
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computational and programming aspects). Experience in machine learning is a requirement. Experience with programming and app development will be emphasized. Personal skills, including independence, abilities
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equivalent degree machine learning or a related area, or must have submitted his/her doctoral thesis for assessment prior to the application deadline. It is a condition of employment that the PhD has been
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. In particular, we are interested in the joint applicability of such models and to what extent simpler models (possibly based on machine learning) can be integrated into full-physics simulation
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on machine learning) can be integrated into full-physics simulation. The successful candidate will contribute to research activities in the CSSR center, and in particular its work package 5. Tasks
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specific research questions. While the group has started to apply machine learning tools to a number of data sets, the seismic network still operates based on conventional tools. Objectives of this position