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borehole electromagnetic data during drilling. This includes the further development and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed
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develop new deep learning algorithms for spatio-temporal medical image analysis with particular focus on learning from limited labelled data. General information about the position. The position is a fixed
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and application of fast solvers for Maxwell’s equations and nonlinear inversion algorithms that we have already developed in a previous PhD project. In addition to electromagnetic geophysics
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. Researchers at Integreat develop theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data. By combining the mathematical and computational cultures, and the
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using advanced mathematical tools. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and
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. This insight opens the door for enjoying the real world. The candidate further develops efficient and robust algorithms for realistic settings in terms of data and computing resources and collaborates to address
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particular to the development and validation of novel computational language models, algorithms, and tools for spoken language-based cognitive tests for low-resource languages, and their integration with
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collaborative skills. Applicants must be proficient in both written and oral English. Experience from one or several of the following areas is an advantage: Developing algorithms for CFD solvers (e.g. OpenFOAM
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at the University of Bergen. The Department hosts the Center for Digital Narrative (CDN) , a Norwegian Centre of Research Excellence. The Center focuses on algorithmic narrativity, new environments and materialities