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- NTNU Norwegian University of Science and Technology
- NTNU - Norwegian University of Science and Technology
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- NHH Norwegian School of Economics
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on optical transmission through falling snow and the models we have are inaccurate. By conducting experiments in Arctic weather over a longer period of time, at different geographic locations, we hope to build
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qualities required for such purposes. Digital terrain models will be used to efficiently map cultural remains under forest canopies. The second project (Mapping Natural Forests in Norway) focuses on mapping
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. The objective of the research is to use machine learning methods to find models of ship trajectories and traffic patterns that can be used to detect anomalies and predict into the future. The basis for this is
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project/work tasks: Development and testing of bioprinted hydrogel scaffolds for bone regeneration Evaluation of cytocompatibility and biosafety in vivo and in different in vitro models Validation
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Maritime Organization (IMO). The Advanced Maritime Ship Operations research group is dedicated to developing and showcasing digital twin models for selected vessels through extensive ship performance and
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- who seek to integrate their perspectives to advance Global Strategy and International Business research. E-mail: bjorn.schmeisser@nhh.no Business Model Innovation Business model innovation (BMI) has
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. The project will quantify how prokaryotic and eukaryotic gene expression patterns influence one another. The candidate will model the relationship between species relative abundances and gene expression to
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science, and translational research models—SHIELD supports research on therapeutic strategies, novel antimicrobial materials, and experimental models that bridge laboratory discoveries to clinical
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the Section for Ethics and Health Economics (ETØK). The position is part of the project “Strengthening health and disease modelling for public health decision making”, funded by the Wellcome Trust. The project
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designing, developing and evaluating systems and models to enhance learning through AI technology. The PhD fellow will engage with developing and evaluating models and agents, as well as, multi-agent networks