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systems. By combining microclimate modelling, remote sensing data, and data-driven methods, the results are integrated into a Digital Twin framework. The research will support predictive risk assessment and
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of maintenance. The project aims to develop an integrated decision-support framework that combines inspection images, sensor data, and engineering interpretation to enable more transparent, evidence-based
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and physical activity influence brain plasticity in regions linked to emotion and memory (the frontal cortex and hippocampus). Integrate all data to uncover how enrichment influences the complex
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in three cities with headquarters in Trondheim. 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
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quantum computing, aiming to solve small, complex sub-problems using Quantum Process Units (QPUs) while leveraging classical High-Performance Computing (HPC) on data-intensive tasks. With dedicated
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three-year PhD–positions related to use of AI for mapping of forest ecosystems. New sensors and increased digitalization generate vast quantities of data that together with advanced statistical methods
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carcinoma as a use case. The successful applicant will develop Bayesian statistical and machine learning methods for treatment response prediction using clinical information, molecular characterizations
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Professional Practice at the Faculty of Nursing and Health Sciences. More information about the programme is available at nord.no. Place of work and internationalisation: The position will be based at one
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, monitoring even the most basic snow characteristics, such as presence of snow cover or snow depth, remains challenging. Most available satellite-based and modelled snow data products, especially for snow depth