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)! Tübingen has a long history of academic excellence (founded in 1477; DNA was discovered here ; linked to 11 Nobel laureates) and is an innovation center in medicine and machine learning. About Eberhard
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computer scientist with programming experience, but no background in science communication - or vice versa - we still encourage you to apply. Your tasks and duties will be a subset of the following
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is connected to the vibrant local ecosystem for data science, machine learning and computational biology in Heidelberg (including ELLIS Life Heidelberg and the AI Health Innovation Cluster ). Your
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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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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, Computer Science or related fields (for PhD); Doctorate in Physics, Computer Science or related fields (for Post-Docs). The positions are funded via the Cluster of Excellence (Machine Learning for Science), the ERC
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reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming languages (C++, Python, or Julia) is highly relevant. Knowledge
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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areas is expected: numerical analysis, scientific computing, model reduction, uncertainty quantification, machine learning, fluid mechanics. Experience with scientific object-oriented programming