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Field
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evaluate large language models (LLMs) assisted methods for extracting, organising and assessing complex scientific information related to materials. The initial application will be phase diagrams and related
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orientation. Relevant projects may make use of large-scale survey data, administrative or register-based data, repeated cross-sectional or longitudinal designs, evaluation studies, or combinations
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heterogeneous sources of information—including remote sensing, forest inventory data, existing forest maps, environmental and climatic data, and emerging large-scale AI representations—can be jointly exploited
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on developing probabilistic latent-variable methods for large and structured biological data, with applications in genomics, spatial transcriptomics, and fluorescence imaging. High-dimensional and structured
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methods, data mining, and machine learning methods. Documented shell script, R, Python, and C programming skills. Documented experience in big data analysis and computational tool/package development
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6 Sep 2026 Job Information Organisation/Company University of Oslo Research Field Physics Researcher Profile Established Researcher (R3) Positions Research Support Positions Application Deadline 15
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Analysis and Computational Methods: Develop and apply computational pipelines for processing large-scale imaging datasets, integrating structural and functional data, and identifying organizational
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data. Experience with FITACF, PyDARN, GUISDAP and RST data analysis tools. Demonstrated experience of working with or developing AI tools for analysis of large datasets. Authorship or co-authorship in
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programming skills. Documented experience in big data analysis. Documented experience in high-throughput sequencing data analysis. Language requirement: Good written and oral English proficiency. English
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. 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 application process here. ... (Video unable to load