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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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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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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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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
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(the final scope will be developed together with the candidate, and it is not necessary to cover all topics): Group fairness: developing and analysing algorithms and metrics for ensuring fair treatment
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, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information
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programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software engineering, information systems, learning technology, HCI, CSCW, IT operations and
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environment in Norway, and offer a wide range of theoretical and applied IT programmes of study at all levels. Our subject areas include hardware, algorithms, visual computing, AI, databases, software
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the fellowship will be hosted by the Department of Mathematical Sciences (https://www.ntnu.edu/imf ). The project is a close collaboration with evolutionary ecologists from the Department of Biology
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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