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interdisciplinary approaches and methods to study biomolecular condensates. The intrinsically interdisciplinary nature of this field poses particular challenges—especially in establishing a shared scientific data
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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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Description The Munich School for Data Science (MUDS) is a joint initiative of Helmholtz Munich, Helmholtz Institute for RNA-based Infection Research (HIRI), and the German Aerospace Center (DLR
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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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Description 3 x Academic Researcher (m/f/d) (TV-L E 13, 100%, Service Location: Clausthal-Zellerfeld) The research group Dependable and Autonomous Cyber-physical Systems (DACS) at the Institute
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, artificial intelligence, and security, with a focus on tools and techniques for constructing reliable, efficient, and secure software. General areas of research include: Artificial intelligence to reason about
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molecular plant physiology and biochemistry to human nutrition, food security, and horticultural production systems, thereby covering the full range from fundamental to applied research. The following
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Description Where: At the Chair for Computational and Theoretical Biology ( CCTB ) and the Center for Artificial Intelligence and Data Science ( CAIDAS ) of the University of Würzburg. Project
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and Data Science (MIDS) at the KU Eichstätt-Ingolstadt. The research group works at the intersection of analysis, modeling and simulation. The advertised position is partly funded by the German Research