600 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions in Norway
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- Integreat -Norwegian Centre for Knowledge-driven Machine Learning
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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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strategic strategic research area on civil security by focusing on the vulnerability assessment of urban environments, sustainability, resilience, and knowledge for a better world (https://www.ntnu.edu/civil
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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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. 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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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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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