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Field
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experience in the field of crowd dynamics, modelling , or data analysis—however, a strong scientific interest is more important to us than prior knowledge Enthusiasm for combining and expanding methodological
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Your Job: In the CrowdING project, you will analyze experimental data from large crowds and develop quantitative measures to describe their spatial structure. To do this, you will use and expand
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Phenorob, we develop novel agrogeophysical methods to obtain noninvasive subsoil information that can be used to advance root phenotyping and soil functions. Soil-root interactions will be analyzed across
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international, interdisciplinary research center on the DESY campus where scientists from ten different university and non-university institutions work together to investigate the structure, dynamics and function
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will be part of a dynamic research team applying advanced geophysical methods to study soil–plant interactions. Your main responsibilities will include: Developing and applying high-resolution time-lapse
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to the studies of protein dynamics. In this project, we seek to understand the structure and dynamics of protein molecules in concentrated solutions. The candidate will use Small-Angle X-ray Scattering (SAXS), X
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to reduce soil erosion. develop a pan-European dynamic soil erosion monitoring system to assess soil erosion status and trends across spatial and temporal scales and promote best management practices
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investigate the structure, dynamics and function of pathogens and their host interactions.The Sondermann lab [Link] is interested in deciphering the molecular processes that determine bacterial interactions in
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on the campus of Forschungszentrum Jülich. Your tasks include in detail: Construction and commissioning of a new test stand for the investigation of the continuous butanediol dehydrogenation under dynamic
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protocols to our Workflow Performing microscopy experiments on sperm dynamics under various controlled environmental conditions. Merging experimental results, simulations, and literature for optimal