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PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage (ref 290702)
27 Nov 2025 Job Information Organisation/Company University of Oslo Research Field Geosciences Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application
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Please note that only shortlisted candidates will be contacted. Qualifications • A doctoral degree (PhD, DPhil, or equivalent) in Epidemiology, Biostatistics, Mathematical Modelling, Health Economics
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research on one or more of the following topics: Interpretability and transparency: Developing methods to understand how language models process information and make decisions, such as sparse autoencoders
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invites applications for a Research Fellow position in the field of battery fire modelling and safety. The successful candidate will join an interdisciplinary research team working on advanced computational
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information, to form relationships for future collaborations and identify potential sources of funds and/or opportunities for collaboration. About You The candidate must have obtained a PhD degree within 3
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write English fluently is a prerequisite. Contacts Applicants seeking further information regarding the PhD position are invited to contact: For information about application requirements and mandatory
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model complex brain data. The ideal applicant will have expertise in either systems neuroscience or NeuroAI/machine learning, particularly in analysis of large-scale neural data. The group places a strong
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on the ethical, legal, cultural, and societal implications of AI in creative fields. See mishmash.no for more information. This PhD position is linked to Work Package 5 in MishMash – AI in the Creative and
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-time position in the Saw Swee Hock School of Public Health: Research Fellow We are looking for research fellows with a quantitative background for ongoing research in Public Health. They will be working
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About the position Position as PhD Research Fellow in ML-assisted reservoir characterization/modelling for CO2 storage in volcano-sedimentary systems available at Department of Geosciences Starting date