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Field
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programs, the university unites the natural and engineering sciences with the humanities, social sciences and medicine. This wide range of disciplines is a special feature, facilitating interdisciplinarity
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on the fundamental processes that control the dynamics of the lithosphere and the design of the earth's surface. The extent and nature of volcanic eruptions are determined by the physical properties of melts and their
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exceptional researchers to join our dynamic team. As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language
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communicator in both Dutch and English ; a natural team player with the ambition to further develop the field of visual techniques. In our international working environment there is an increasing amount
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The Senckenberg Society for Nature Research (Senckenberg Gesellschaft für Naturforschung, SGN) was founded in 1817 and is one of the most important research institutions around biological diversity
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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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trade-offs of upscaling Offshore Wind Farms (OWFs) in the context of climate change and the ongoing food and nature transitions in the North Sea. The project has an interdisciplinary consortium of world
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to 1,500 EUR per month. Academic admission requirements Master's degree or equivalent in the life sciences, mathematics, computer sciences, statistics, biophysics, or a related field Language requirements
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of on-site construction production processes, as well as sustainable development. You will also demonstrate independence, creativity, and strong collaboration and analytical skills. Research environment
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programming background with expierence in using Python, matlab, and/or Java, etc. a good command of German and English, both for teaching and for the preparation of research proposals and publications process