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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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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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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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– 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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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
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physics, to experimental biophysics and biochemistry, and, to cell and molecular biology involving data science. A position comprises 65-75 % of the fulltime weekly hours and is limited until March 31, 2030
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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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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
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Several PhD positions (f/m/d) in International Research Training Group (iRTG) limits2vision Full PhD
topics that focus on the interplay between genetics, metabolism, and information processing. Specifically, the projects in the limits2vision programme aim to systematically unravel the mechanisms