319 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" Fellowship positions in Norway
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- University of Oslo
- UiT The Arctic University of Norway
- University of Stavanger
- University of Bergen
- NTNU - Norwegian University of Science and Technology
- University of Agder
- NTNU Norwegian University of Science and Technology
- OsloMet – Oslo Metropolitan University
- University of Inland Norway
- CICERO Center for International Climate Research
- CMI - Chr. Michelsen Institute
- Høgskulen i Volda
- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
- NORCE Norwegian Research Centre
- Nord University
- Norwegian Institute of Bioeconomy Research
- OsloMet - storbyuniversitetet
- Simula Research Laboratory
- Simula UiB
- The Norwegian Polar Institute
- University of Agder (UiA)
- University of Oslo;
- Østfold University College
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recently funded centre of excellence (Integreat). Integreat collects scientists from statistics and computer science and offers a flourishing machine learning community, including many PhDs and PostDocs
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of the post. Candidates without a master’s degree have until 1st of July 2026 to complete the final exam. Strong programming and artificial intelligence/machine learning skills. The candidate’s research
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. Further information about the research groups can be found at: https://www.mn.uio.no/math/english/research/groups/algebra/index.html https://www.mn.uio.no/math/english/research/groups/geometry-topology
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kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several stakeholders: i) architects and urban
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are reshaping how we learn, work and participate in democracy, our centre tackles the promise and peril of hybrid intelligence—human and machine working and learning together. AI LEARN’s mission is to establish
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laboratory analytical methods (e.g., chromatography, mass spectrometry). Familiarity with AI or machine learning applications relevant to environmental data analysis. Basic knowledge of GIS/mapping tools
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understanding of how acoustic waves are generated and transmitted in wells. The LeDAS project aims to overcome these challenges by combining physical modelling, advanced signal processing, and machine learning in
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qualifications: A strong background in algebraic topology. Experience in any of the following: Higher category theory, stable homotopy theory, simplicial methods. An interest in computer algebra and programming
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to the international initiative “Antarctic InSync.” For more information, see: https://ic3.uit.no/ . The position is based in the Marine Ecology section of the Research Department and will involve collaboration within a
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(NELO), revealing the branchial cavity as an important region of the fish immune system. (https://www.science.org/doi/10.1126/sciadv.adj0101 ) (https://www.frontiersin.org/journals/immunology/articles