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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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Description At the Leibniz Institute of Plant Biochemistry in the Department of Bioorganic Chemistry a position is available for a PhD in Machine Learning for Enzyme Design (m/f/d) (Salary group E13
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The research group Cyber-Physical Systems of Prof. Matthias Althoff at the Technical University of Munich offers a PhD position in the area of automatic formal verification of cyber-physical systems
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, Computer Science, Artificial Intelligence, Theoretical Computer Science, Computer Engineering, Practical Computer Science Description Description The CISPA Helmholtz Center for Information Security is
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Mathematics, Technomathematics, Computer Science, Engineering Informatics, Theoretical Computer Science, Physics Description Description The research group Cyber-Physical Systems of Prof. Matthias Althoff
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Description In the research group Dependable and Autonomous Cyber-physical Systems (DACS) on Institute for Software and Systems Engineering (ISSE) at Clausthal University of Technology has
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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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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with