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and society. We are a major part in implementing the 2030 vision of the Faculty of Medicine, i.e. to become leading within digital health and well-known for doctors and engineers finding solutions
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across news outlets, social media platforms, and individual news diets, drawing on, among other data sources, data donations from individuals and automated content analyses. SP2 will examine how people
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cell walls (i.e. the pores) of biogenic materials, and distribution of critical water in rigid materials prone to frost damage. The project is expected to deliver models for moisture transfer and storage
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Intelligence, Data Science, Robotics or any other relevant field, prior to receiving admission into this PhD program, i.e., we accept applications from candidates expecting to finalize their studies within
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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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. The duration of the position is three years. Your work tasks The PhD project is centred around advanced CFD modelling of liquid green fuel (methanol and ammonia) combustion under engine-like conditions, i.e., in
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underlying gene expression, as well as a clear view of their medical importance and potential for a future research carreer. Information on CGEN can be found at: https://cgen.ku.dk/ Information
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in-situ monitoring data, ex-situ characterization data and failure data from aggressive loading of AM samples. The activities will span across exploratory data analysis, mathematical model building
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research on architectures and methods for the real-time delivery of EO data from dense nanosatellite/CubeSat constellations and to develop innovative GNSS-based sensing methods and AI models to detect a
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the Center for Pharmaceutical Data Science Education (CPDSE) and will be conducted under the supervision of Associate Professor Casper Steinmann . The project concerns physics-based computational modeling