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be associated with the new national AI LEARN Centre at SLATE. The position is for a fixed term of four years, with the inclusion of career development work (e.g., teaching, project work) accounting
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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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”. The appointment is to be made in accordance with NTNUs guidelines for recruitment positions and Regulations for the degrees philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work
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for the degrees philosophiae doctor (ph.d.) and philosophiae doctor (ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred
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/Machine Learning (AI-ML) approaches to meeting this challenge. Possible topics include, but are not limited to: storylines for plausible narratives of regional climate change, novel algorithms for rare
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for plausible narratives of regional climate change, novel algorithms for rare event sampling or ensemble boosting, and the development and use of hybrid climate models combining physics-based and ML components
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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