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technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models, and algorithms that integrate general and domain-specific knowledge with data
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of algorithms for medical image analysis. The successful candidate will investigate computational complexity, stability, and numerical summaries of multiparameter persistence, as well as applications to medical
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mathematical and computational engine of Artificial Intelligence (AI), and therefore it is a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat
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analysing algorithms and metrics for ensuring fair treatment of groups defined by protected attributes (e.g. gender, age, ethnicity, …). Theoretical relations between fairness notions: studying
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the Cortex (https://www.ntnu.edu/kavli/centre-for-algorithms-in-the-cortex) will be funded for 10 years by the Norwegian Research Council. The scientific goal of the Kavli Institute for Systems Neuroscience
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for probabilistic unsupervised learning for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high
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-driven surrogate models for real-time reconstruction and forward simulations. Create numerical algorithms for physics reconstruction using sparse data. Implement assimilation pipelines which integrate
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for structured biological data. The successful candidate will: Develop probabilistic factor models and scalable inference algorithms for structured biological (multi-view) high-dimensional data. Develop modular
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to the IE faculty's Doctoral Programme (https://www.ntnu.edu/ie/research/phd/ ), see Section 6-1 of the PhD regulations for more information. You must have a relevant Master's degree in Computer Science and
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companies. The research will integrate techniques of numerical analysis and structure-preserving algorithms to generative modeling in AI. It will build upon the work done at IMF and SINTEF in this field. We