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, which are based on AAU's problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within
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. Experience in modeling biological processes. Experience in use of process simulation tools such as Matlab, Aquasim, Superpro Designer or similar. Expertise within fermentation technology and/or gas
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complex problems, which require high-level modelling, data analysis and management capabilities as well as developing solution algorithms, applying mathematical and computational approaches. The group has a
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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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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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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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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