573 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Norway
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. The successful applicant must be able to teach at all levels and to supervise Master and PhD students. The successful applicant may furthermore be required to take on other teaching duties and administrative tasks
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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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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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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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Norwegian master’s degree. Please see https://hkdir.no/en/ for more information about HK-dir’s general recognition. The review process by HK-dir may take some time. Therefore, please submit your application
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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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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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(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