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-education-system/grading-system/?set_language=en ). Additionally, the candidate must include: a brief curriculum vitae (CV), a list of papers and publications (if any are available), and one copy of a
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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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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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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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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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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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linked data Sensors as part of Internet of Things (IoT) and integration of sensory information in simulation models as part of Digital Building Twins (DBT) during run-time Life cycle and sustainability
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group at CIE. The aim of the position is to build strong knowledge and competencies within the field of electrochemical storage device design, simulation and testing. Job description You will conduct