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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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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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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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for Catalysis and Organic Chemistry at the Department of Chemistry. The group has extensive experience in computational modelling, reaction mechanisms, and machine learning for catalyst design and discovery. Nova
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four years are expected to acquire basic pedagogical competency during their fellowship period within the duty component of 25 %. Project description and work tasks Particle accelerators are engines
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Is the Job related to staff position within a Research Infrastructure? No Offer Description You are keen on contributing to new advances in deep learning methodology for imaging for monitoring marine
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: Preference Learning for LLMs Apply for this job See advertisement About the position Integreat – the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo – invites applications
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machine learning and AI techniques to improve prediction of contaminant transport, sediment dynamics, and ecosystem exposure in complex fjord environments. The research will benefit from extensive
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position as Postdoctoral Fellow in law at the UiS School of Business and Law, Department of Accounting and Law. The Postdoctoral Fellow will be affiliated with the research project AUTO-MARE – Autonomous
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machine learning methods and apply them in an interdisciplinary research environment spanning physics, neuroscience and computational science. You will be expected to participate both in the activities