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experience with spatial data analysis using GIS tools or spatial libraries and familiarity with common land-use datasets would be advantageous familiarity with environmental or agricultural economics research
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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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dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven
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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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obtaining academic qualifications as well as courses on development of competences at university as a workplace and orientation with regard to further career steps in science, industry and society
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reporter assays Integrate omics data to identify functional variants affecting spermatogenesis REQUIREMENTS: A Master’s degree in Biology, Molecular Medicine, Biochemistry, Biotechnology, or a related
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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University Munich operates the high flux Neutron Source Heinz Maier-Leibnitz (FRM II) located at the science campus in Garching, Germany. The neutron source itself, its research instruments as
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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