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on performance and project needs. **Qualifications** • For Doctoral Candidates: Master’s degree in Computer Science, Information Systems, or Mathematics. **Applicants must demonstrate:** • An excellent academic
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at the interface of data science and the scientific domains pursued at the three participating Helmholtz centers. Methodologically, a broad range of topics is covered, from large-scale data management to data mining
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of Prof. Dr. Frank Cichos and Dr. Nico Scherf (Max Planck Institute for Human Cognition and Brain Sciences). The position is part of a collaborative project in the Center for Scalable Data Analytics and
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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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Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities and the German
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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Research Center (CRC) “Data-driven agile planning for responsible mobility” (AgiMo), funded by the German Research Foundation (DFG). This interdisciplinary center, involving four universities and the German
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whether it may fit your interests, please read some recent papers by our lab before you apply. Additional Information CISPA and the University of Stuttgart have a large interest in increasing the number
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activities of the Schlundt lab here . We are excellently embedded in a large research infrastructure and with the neighboring departments as well as one of Germany’s best university hospitals. The full job
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machine‑learning or data‑analytics tools High‑level programming skills (Python, R, Julia) to build, test, and optimize models of geochemical systems Interest in large‑scale computational simulations (e.g