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. The project combines advanced computational mechanics, nonlinear finite element analysis and fluid–structure interaction to address critical challenges in civil protection and societal resilience. About the
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Basis of Design for tunnels with concrete lining at disposal depth, establishing a transparent and traceable set of design requirements. You will work on the data analysis underlying the project's
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. Required PhD student academic qualifications: Honours/Msc degree in microbiology/bioinformatics, with specific emphasis on functional microbial multi-omic data analysis. Knowledge of a programming language
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explore unconventional ideas, develop computer algorithms for data analysis, create new experimental approaches, and apply the technique in areas like biomedicine, materials science, and geology. My group
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communication skills in Swedish, Strong knowledge of electric power engineering, power electronics, and power system analysis, Experience of modelling, simulation, and experimental work. In an overall assessment
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collaboration skills. Effective analytical and problem-solving abilities. Ability to manage multiple projects and meet deadlines. Proficiency in research methodologies and data analysis. Ability to work
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tweezers, (iv) quantitative image processing, data analysis and modeling. The project is funded by the MARIE SKŁODOWSKA CURIE ACTIONS (MSCA) Doctoral Network (DN) MOtorized NAnomachines: fundamentaLs
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty
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across copper–silicon interfaces. You will work with characterization methods including SEM, EBSD, XRD, thermal conductivity analysis, and thermo-mechanical testing. The project also includes
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levels. A central component of your work will be the collection and analysis of qualitative empirical data. The empirical work will be based on in-depth case studies of firms operating within the Danish