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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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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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– 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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with shallow water equations). Python coding for workflow control, data pre- and post-processing as well as model calibration and validation. High-performance computing (HPC) for running test cases and
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-ethnic environment with sensitivity and respect for diversity Desirable: Experience in cheminformatics, molecular modeling, or enzyme mechanisms Familiarity with databases, data mining, and knowledge
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geriatric care in the Strukturwandelregion (former coal-mining region) of Saxony-Anhalt. The successful candidate will observe, follow, and engage various stakeholders (tech companies, care workers, local
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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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temporarily and continue with the data entry at a later date. Applications must be submitted by 15 October 2025, 00:00 CET. BerGSAS will invite shortlisted candidates to an online interview within two months
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biochemical techniques to study details of antigen recognition and effector functions of autoantibodies Engage in data analysis and collaborate with computational scientists. Your qualifications: MSc