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- University of Oslo
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- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NTNU Norwegian University of Science and Technology
- OsloMet – Oslo Metropolitan University
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the use of modern machine‑learning methods within applied mathematics—particularly physics‑informed learning, anomaly detection, data‑driven modelling, and the construction of surrogate models grounded in
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conducts research that contributes to the sustainability of the Norwegian welfare state and the metropolitan region. The Faculty of Technology, Art and Design (TKD) offers higher education and research and
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numerical models and machine learning tools to predict loads, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches
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, interpretation of modelling results, and publication-driven research Ability to work independently, efficiently, and with clear scientific judgment Fluent oral and written communication skills in English Desired
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Is the Job related to staff position within a Research Infrastructure? No Offer Description The Language Technology Group (LTG) at the UiO Department of Informatics (IFI) is an inter-nationally
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, assess structural responses, and identify damage under extreme conditions. By combining computational simulations with data-driven approaches, the project will provide practical models for hazard
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damage models. The candidate will contribute to an ongoing research initiative aimed at advancing NDT-based monitoring technology, including sensor development, signal processing, and experimental
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of Artificial Intelligence (AI), and therefore a fundamental force of technological progress in our increasingly digital, data- and algorithm-driven world. Integreat develops theories, methods, models and
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position (100%, three years) is related to finance and insurance. The theme of the research project will lie within areas such as: simulation and risk modelling using advanced statistical and machine
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invites applicants for a position as Postdoctoral Fellow in Computational Materials Science at the Faculty of Technology and Science, Department of Mathematics and Physics The position is vacant from August