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Field
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analysis will be used to study the seismic response of prototype structures for different scenarios. Hence, the project integrates advanced element-scale, model-scale and in-situ testing with state
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description This project focuses on developing, analyzing and using probabilistic methods for dynamic phenomena evolving over space and time based on measurements from different and complementary sources. We
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behavior during transport, compression, and fueling under realistic port conditions. Analysis of intermediate storage concepts tailored to different port profiles. Evaluation of energy efficiency and
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, quantum optics is an advantage. General experience of experimental physics is preferred. Experience in data analysis using Python. The outcomes of this project will be disseminated to the scientific
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and/or data processing in Python. Knowledge about solid state physics. Knowledge about magnetic materials. Personal characteristics To complete a doctoral degree (PhD), it is important that you are able
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a difference: whether you’re exploring the future through research, inspiring students in the classroom, or helping shape everything that makes our education and research possible. PhD in
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between passport templates and openLCA, enabling rapid recalculation of environmental impacts under different reuse or recycling scenarios. This approach prioritizes the methodical adaptation of existing
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models. Experience (or strong willingness to learn) in programming and data analysis (e.g. Python, MATLAB, R, Fortran, or similar). Curiosity and motivation to work on fire emissions, air quality, and
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candidates must meet the requirements for an MSc degree. Good verbal and written communication skills in English are required. Other advantageous qualities include experience with coding (Python\Matlab) and
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of upscaling of permafrost thaw and greenhouse gas emissions. The candidate will work with ample of existing observational data at different levels to upscale the processes and quantify larger scale greenhouse