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- NTNU Norwegian University of Science and Technology
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. This is a term position with a duration of 3 years. The successful PhD candidate will work in a team with several researchers/professors including international collaborators and another PhD at the Faculty
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“Bayesian Enhanced Tensor Factorization Embedding Structure (BETTER)”, and this PhD project specifically aims at developing a unified, scalable, and interpretable framework for tensor analysis. Specifically
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Experience with organic pollutant analysis in wildlife samples Field work experience Experience with running linear models in R Experience with PFAS analysis is an advantage Experience in teaching and/or co
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part of a dynamic research team, joining the REACT-Lab (Renewable Energy and Advanced Construction Technologies Laboratory) and the URGENT (USN Research Group in Energy and Environmental Technology
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three cities with headquarters in Trondheim. At NTNU, 9,000 employees and 43,000 students work to create knowledge for a better world. You will find more information about working at NTNU and the
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the analysis of linked health registries though the development, implementation and application of methods for causal inference in time-to-event outcomes. For more information and how to apply: https
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Fotograf Morten Hjertø 30th April 2026 Languages English English English The Department of Ocean Operations and Civil Engineering has a vacancy for a PhD Candidate in AI-Enabled Uncertainty Analysis
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analysis and/or advanced algebra or algebraic topology. Knowledge and experience of machine learning. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able to: Work
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well as several associated partners (https://www.nnrc.uio.no/english/research-themes/rt-5/ ). The PhD candidate will be part of a dynamic and productive academic team with a large international network covering
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vitro embryo production (IVEP), embryo transfer, and competence building within gene editing. The PhD candidate will become part of an interdisciplinary research environment with expertise in veterinary