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applications of data science and artificial intelligence. In addition, service-oriented solutions are developed and there is close cooperation with a large number of partner organizations from science and
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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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resource-efficiency requirements. This collaborative doctoral project brings together the Institute of Advanced Simulation – Materials Data Science and Informatics (IAS-9) and the Institute of Energy
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biology, cell biology, biochemistry, and plant-microbe interaction research come together to advance sustainable agriculture and reduce reliance on pesticides and mineral fertilizers. Further information
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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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center, CRC 1719 ChemPrint “Next-generation printed semiconductors: Atomic-level engineering via molecular surface chemistry”. Your tasks Develop new approaches for electrodeposition of metals
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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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- 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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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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(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