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Field
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mathematical modeling; fundamental understanding of fluid mechanics and soft matter physics; good quantitative skills and strong analytical capabilities; proven experience with experimental image and data
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engineering, or in a closely related discipline; a strong and proven affinity with experimental techniques and mathematical modeling; fundamental understanding of fluid mechanics and soft matter physics; good
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Vacancies PhD position on the design and fabrication of MEMS drag force-based flow and fluid composition sensors Key takeaways In this project, we will combine well-known thermal flow sensing
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: reduced-order models (ROMs) and input-output models derived from high-fidelity Computational Fluid Dynamics (CFD) models; data-based models determined from training/calibration data by system/parameter
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, postdoctoral researchers, and technicians is expected.
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have experience with experimental work? Are you challenged by building (parts of) an experimental setups? Knowledge on fluid mechanics, physical transport phenomena and/or phase changes are considered
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fluids, such as in serum and plasma in order to determine their stability upon administration and characterize the layer of molecules adsorbed on their surface (the biomolecule corona
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experiment at the LHC. The project will be conducted in close collaboration with Dr Flavia de Almeida Dias and a postdoctoral researcher in experimental particle physics. Your appointment will be for four
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experiment at the LHC. The project will be conducted in close collaboration with Dr Flavia de Almeida Dias and a postdoctoral researcher in experimental particle physics. Your appointment will be for four
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and group activities. Collaboration with other PhD candidates, postdoctoral researchers and other faculty member will be encouraged. At the end of the PhD program the candidate will be an expert in