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challenges and decision-making under uncertainty. Ability to translate conceptual models to their mathematical formulation and to test them with numerical and simulation experiments. Excellent communication in
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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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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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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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. Development of numerical models for system descriptions. Lab-scale tests of a number of UV-AOPs (eg. VUV, UV/H2O2 and UV/O3) using a collimated beam approach. The effect of water composition on the AOP
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breast cancer while it is early-stage and treatable. This one-size-fits-all screening saves lives, but also has drawbacks in terms of false positives, false negatives, and over-diagnosis. Simulation
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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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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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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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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