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- University of Oslo
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- The Peace Research Institute Oslo (PRIO)
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/Qualifications To strengthen our research on the impacts of conflict, PRIO seeks a motivated Junior Data Developer with competence in design and maintenance of databases and machine learning. The successful
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SFI FAST: PhD position in Microstructure/texture evolution during extrusion of scrap-based Aluminium
(as machine learning techniques, etc.). Personal characteristics In the evaluation of which candidate is best qualified for the PhD position, emphasis will be placed on education, experience and
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systems to reason more coherently about ship designs, reducing ambiguity in the data available to machine‑learning systems, and supports explainability by grounding AI outputs in a known structure. This
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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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models with drone imagery using machine learning techniques and data assimilation. The work will involve collaboration with an interdisciplinary team of researchers, engineers, and local stakeholders in a
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research
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dissertated before the start-up date of the position. A research profile with relevant experience in biological sequence analysis, with complementary skills in machine learning or other relevant algorithms. A
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of Visual Intelligence is to develop novel, innovative solutions based on deep learning to extract knowledge from complex image data. Deep learning, aided by machine learning techniques in general, has led
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(ph.d.) in artistic development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning
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interest in social science applications, and with strong competence in statistics and machine learning. The successful candidate will develop predictive models using machine learning and work alongside other