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based on Machine Learning (ML) emulators have taken the weather predictions research by storm, as they run faster and use less energy than traditional approaches: numerical models based on physical
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the Department). The position is financed by the University of Bergen. About the project/work tasks The PhD project aims to investigate how methods from Scientific Machine Learning (SciML) can enhance modelling
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qualifications will strengthen the application: Experience with AI or machine learning applied to environmental systems Experience with coastal circulation modelling tools (e.g., Delft3D, MIKE, ROMS, FVCOM
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generated synthetic representations. The project will also explore machine-learning approaches and efficient imaging strategies, including reconstruction of three-dimensional pore structures from radiography
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, wearable physiological sensing, and machine learning to uncover how factors like fatigue and cognitive workload impact technician performance. Join us to develop predictive models that predict human error
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representations. The project will also explore machine-learning approaches and efficient imaging strategies, including reconstruction of three-dimensional pore structures from radiography. By linking defect
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). The position is subject to financing by the University of Bergen. About the project/work tasks Geometric Deep Learning (GDL) is a branch of machine learning that develops neural network models by explicitly
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Is the Job related to staff position within a Research Infrastructure? No Offer Description Integreat – the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo invites
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grant that focuses on modeling spatio-temporal medical image analysis with a particular focus on learning from limited labelled data. Here you will be a part of the UiT Machine Learning Group and will
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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