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of the existing theories of turbulence and attempt to synthesize new theory based on the empirical result. You will be part of a research group that works on different aspects of turbulence, including theory
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mathematical and analytical models to predict coil loss, facilitating the optimal design of HPMCs Constructing a large-signal platform to measure coil loss of HPMCs Exploring innovative solutions, such as new
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, applied mathematics and computational sciences with a strong focus on computational humanities research. The project leverages an extensive dataset of digitized books, newspapers, and visual artworks
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interdisciplinary university environment, marked by diversity with respect to theory, method, and area of study in research and education. Our research is characterized by double impact, i.e. by the highest academic
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, applied mathematics and computational sciences with a strong focus on computational humanities research. The project leverages an extensive dataset of digitized books, newspapers, and visual artworks
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Job Description As part of expanding the Centre for Visual Data Science , the Department of Mathematics and Computer Science at the University of Southern Denmark, Odense, invites applications for a
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experiments. You will also support analysis of the measurement data in novel ways to test the validity of the existing theories of turbulence and attempt to synthesize new theory based on the empirical result
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project participants is expected to ensure synergy between the sub-projects (Ph.d.-student, PI and postdoc) through method and theory development and a special issue on sleep. Department of Media, Design
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will collaborate with other team members working on novel high-resolution microscopy techniques to experimentally quantify transition probabilities, alongside density functional theory (DFT) calculations
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, geophysics, mathematical modelling, or related fields. The ideal candidate should have: Experience with numerical climate models (such as EC-Earth or similar GCMs). Advanced programming skills in Python