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sheet evolution, methane hydrate fluxes, or applying machine learning to geosciences to reconstruct glacial histories and project future ice sheet behavior. Please read this interview for more details
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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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for machine learning models to optimise membrane properties, structure, and fabrication. The fellow will play a key role in the experimental part of the project, including: Preparation and characterisation
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separation on commercial recordings and extracting audio features (onsets, pitch, harmony, dynamics); curating datasets; and integrating machine learning approaches to complement rule-based methods. For more
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of the researchers of the DKM group are also affiliated with the Norwegian Centre for Knowledge-driven Machine Learning (Integreat) . The candidate is expected to join Integreat and strengthen the interdisciplinary
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University of Oslo as a PhD Research Fellow in Machine Learning, tackling real-world data challenges! PhD Research Fellow in Trustworthy Machine Learning Apply for this job See advertisement About the position
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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computational modeling to identify bacterial strains and metabolites that promote or hinder probiotic establishment. By combining multi-omics data with systems biology and machine learning approaches
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UiO/Anders Lien 24th March 2026 Languages English English English Join the inclusive University of Oslo as a PhD Research Fellow in Machine Learning, tackling real-world data challenges! PhD
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teaching and learning. The Faculty consists of six departments as well as a Faculty administration. Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/296315/postdoctoral-fellow-in-mo