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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 Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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Several PhD positions (f/m/d) in International Research Training Group (iRTG) limits2vision Full PhD
Description Offer Description PhD student positions will become available in the Institute for Ophthalmic Research (IOR) at the University of Tübingen (Germany) and the Institut de la Vision (IDV
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. Correlating experimental, ab initio and multi-scale simulation as well as machine learning techniques is central to our mission: Development and application of advanced simulation techniques to explore and
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Mathematics/ Approximation Theory to be filled by the earliest possible starting date. The Chair of Applied Mathematics, headed by Prof. Marcel Oliver, is part of the Mathematical Institute for Machine Learning
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that exhibit emergent turbulent behaviors, and (2) disordered optical media that process information through complex light scattering patterns. Using advanced imaging, machine learning techniques, and real-time
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and data analytics (including machine learning and deep learning); from high-performance computing to high-performance analytics; from data integration to data-related topics such as uncertainty
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Description Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI ( baiome.org ) to complement our lively and enthusiastic team of machine
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direction (possibly forming spontaneous “lanes”), crossing, and opposite flows. For single-lane vehicular traffic, the model should revert to a car-following model. In cooperation with the supervisor Dr