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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | about 5 hours ago
process models for electrified methanol processes under fluctuating power supply from renewable sources # Simulation and optimization of the operating behavior of flexible systems, including control and
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edge of energy systems and computational engineering, developing scalable methods to simulate and secure IBR-dominated grids. Your key responsibilities include: Conducting large-scale simulations
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the area of machine learning and computer simulations. The focus of the PhD project will lie on developing machine learning models for clustering, classification, regression and reinforcement tasks to work
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response to climate forcings for different past climates. · Perform and analyze global model simulations. · Collaborate with IPSL Earth System model developers to ensure consistent integration
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. Proficiency in modelling using differential equations is required. Candidates are expected to have experience in developing and implementing computational models for computer simulations. Software development
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biologic therapy, integrating data from clinical trials and real-world studies. The model will be used to simulate and evaluate optimized dosing strategies for special populations, including hard-to-treat
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contribute to a major research project to improve our understanding of macroplastic pollution in coastal seas. Working at the intersection of numerical modelling and observations, you will develop simulations
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backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular Networks, and ICT Services
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 6 hours ago
assimilation Integration (JEDI) framework for atmospheric data assimilation Develop machine learning foundation models based on simulated observations from high fidelity atmospheric simulations for developing
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synaptic resilience and the reliability of synaptic responses. The work primarily involves mathematical modeling and numerical simulation, but also the analysis of experimental datasets for model validation