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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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. 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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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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completed, a certified/signed copy of a recent transcript of records or a written statement from the institution or supervisor is accepted. Other information for consideration, e.g., BSc/MSc thesis
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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