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be working primarily with scientific machine learning methods, including symbolic regression and neural networks. You will apply the algorithms to the discovery of new models in different fields
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environmental changes, agricultural management, and ecosystem sustainability Experience with deep learning, radiative transfer modeling and ecosystem modeling Teaching and supervision experience Who we
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experience in one or more of the following areas: Reinforcement Learning / Deep Reinforcement Learning Fine-tuning and Application of Large Language Models Time-Series Data Prediction and Modeling Intelligent
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% for PhDs and TV-L E14, 100% for PostDocs; 45k - 57k Euro / year + benefits). For interns, we offer a stipend to cover living expenses. Click here to learn more about our research. Topic / Area: The
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard