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- looking. Sensor technology plays a key role in this transformation, enabling real-time monitoring, automation, and intelligent decision-making. Despite these needs, many water treatment processes still rely
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partnership with the German Federal Waterways Engineering and Research Institute (BAW); building a fully coupled model that simulates surface hydraulics and subsurface flow with relevant turbulence models and
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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available on site for the development of suitable radiotracers. One focus of the work is on the use and evaluation of large tomographic data sets to derive parameter data for reactive transport modeling
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or directly inside the cell. This approach requires biochemistry or cell biology for the sample preparation and scripting skills for the ET data processing. For more information, please read PMID33762348
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highly collaborative and interdisciplinary research environment, where you'll work alongside experts from fields such as transport and urban planning, engineering, data science, computer science. Skill
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/Diploma) in the field of Biochemistry, Biology, Pharmacy or Chemistry or related field Experience in experimental laboratory work Excellent knowledge of a broad range of biochemical, cell and molecular as
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Economics offers a highly international and stimulating work environment that promotes individual creativity and effective teamwork with a clear focus on quality output. More information about the group is
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(0)511 762 3623 E-Mail: peth at ifbk.uni-hannover.de Web: https://www.iesw.uni-hannover.de/en/research/main-research-areas/soil-science Legal notice: The information on this website is provided
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(0)511 762 3623 E-Mail: peth at ifbk.uni-hannover.de Web: https://www.iesw.uni-hannover.de/en/research/main-research-areas/soil-science Legal notice: The information on this website is provided