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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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engineering, computer science or a comparable subject You have good experience in Python You have basic knowledge of the theory and methods in machine learning Good language skills in German and/or English What
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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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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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/d) in Energy Informatics, specifically for a DFG project in wind power forecasting using machine learning. You are passionate about applying cutting-edge information technology to solve the energy and
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processing and machine learning methods, and big data analytics solutions to extract highly accurate large-scale geo-information from big Earth observation data. Our team aims at tackling societal grand
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1
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Field of study: computer science, mathematics, software design, software engineering, technical computer science or comparable. Machine Learning (ML) models are reaching a maturity level that allows
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equipment and the newest technology The chance to independently prepare and work on your tasks An exciting work with personal responsibility in the research field of machine learning for material sciences
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD