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Field
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will be involved in exploring the models, designing, and measureing CMOS-based interface (coherently control, readout, and biasing) to quantum bits: Conduct a thorough review of recent research in
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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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work with fish behavior, engineering geology, turbine design, variable speed operation, etc. It involves fundamental research including a literature study and CFD modelling with the use of real case
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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 development of multiscale computational models for simulating crack propagation and establishing reliable methods to predict the residual strength of composite structures. The simulations, performed in Ansys
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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
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/or application areas such as the ones listed below: CROSS-DISCIPLINARY RESEARCH Nanomaterials &Nanofabrication Nanocharacterisation Modelling and simulation APPLICATION AREAS OF RESEARCH Health Energy
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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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corrosion-fatigue conditions by integrating multiscale physics-based models combined with mesoscale experimental tests. This research will study the effects of corrosion-induced changes in composition
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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