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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 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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within the Institute of Theoretical Computer Science at TU Dresden. The main research area is the design and analysis of algorithms and data structures, with possible focus areas including randomized
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field • Is fluent in English • Is interested in finding innovative, creative solutions • Has good programming/data analysis skills • Is experienced or at least strongly interested in one
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. Collaboration between students and researchers at the partner institutions is facilitated through a lively exchange program. The professional training of students includes data science as a supporting component
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Description As part of the German government's artificial intelligence (AI) strategy, the successful Saxon competence center ScaDS.AI Dresden/Leipzig (Center for Scalable Data Analytics and