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, predict, and manage them remains fragmented across disciplines. The Understanding and Predicting Impacts of Climate Extremes under Global Change Doctoral Network (CLIMES DN) (https://www.climes.se/climesdn
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project involves interdisciplinary research at the interface of computer science and mathematics, with a focus on bivariate molecular machine learning for modeling molecular interactions and properties
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energy system optimization models including, e.g., reservoir productivity predictions, novel surface processes for CRM extraction, CO₂ reinjection, and reconversion of decommissioned oil wells Economic
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for the built environment. Particular emphasis is placed on artificial intelligence in construction, building information modelling, point cloud capturing and processing, as well as construction robotics. The PhD
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of Digital Agriculture is engaged in simulation models of plant stands to improve plant system understanding and its control and optimization. Our research links Artificial Intelligence methods
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therapeutics by protein design. This project will apply cutting-edge generative AI methods—including protein design, structure–function prediction, and multimodal learning—to develop and optimize a new
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» Applied physics Technology » Medical technology Engineering » Biomedical engineering Computer science » Modelling tools Economics » Health economics Biological sciences » Other Researcher Profile First
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partner from data sciences provides data management and AI based Image analysis, an internal simulations group working on quantitative models to reproduce and predict experimental data, and an internal