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about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its
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preferably has strong programming skills and experience with the modeling and simulations of fluid or solid mechanics or ice sheet flow and deformation (for example by use of finite element/volume methods
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will conduct sampling, and apply experimental methods such as metagenomics and metatranscriptomics, linked to soil and emission data to help create predictive models. Within a broader framework, your
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with colleagues from RWTH Aachen and visit their facilities. The aim in this PhD project is to conceptualize and model the asynchronous architecture for future power grids. As we depart away from
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that dynamically alter the detrapping and recombination probabilities. The aim of this project is to overcome these limitations by developing a Monte Carlo simulation model that treats each charge carrier and its
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delivering influenza vaccination through intramuscular and intranasal routes, which will be compared to a live influenza human challenge infection model in humans. Methodology will involve implementation
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failure analysis using advanced finite element models and simulation techniques. This is enabled by digital and sensor technologies such as artificial intelligence, computer vision, drones, and robotics
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results with AI models and system simulations to create a digital twin of the PtX process for predictive optimization and scenario analysis. Funding This PhD position is generously funded through the Villum
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to the PhD project ie. processing and analysis of dietary intake data, statistical analyses (eg. linear mixed models) as well as evaluation of child growth and body composition data. Relevant publications
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are developed, modelled and controlled. You will create novel adaptative, physics-informed models that tightly integrate thermo-fluid dynamic laws, deep learning neural networks, and experimental data. A key