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will extend this framework to the constitutive modeling of porous and cellular materials, such as polymer and metal foams, and to industry-sponsored projects on the mechanical testing and
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response across scales. The project combines physics-based modeling, simulation, theoretical reasoning, and quantitative comparison with experiments in collaboration with partners from the ETH Department of
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in energy systems engineering, with an emphasis on industrial energy systems, energy management, techno-economic analysis, modeling, simulation, optimization, and advanced control. The position will
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
postdoctoral position in the Cardiovascular Modeling and Simulation Laboratory (https://griffith.web.unc.edu). This position would support projects on (1) cardiac digital twins for heart failure and/or (2
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 19 days ago
postdoctoral position in the Cardiovascular Modeling and Simulation Laboratory (https://griffith.web.unc.edu). This position would support projects on (1) cardiac digital twins for heart failure and/or (2
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analysis using tools such as NetworkX Graph‑based ML or graph neural networks (GNNs) is a plus Experience with modeling and simulation techniques, such as: Network, agent‑based, or discrete‑event simulation
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description This postdoctoral R&D project will focus on the modeling and analysis of hydrogen (H₂) gas bubble
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interdisciplinary work and team collaboration. Skills or experiences in the following areas will be considered as a plus : - Physical modeling and simulation; -Scientific computing and partial differential
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Computational Cardiac Modeling (CaMo) group, Karlsruhe Institute of Technology (KIT), Germany. GSP techniques will be validated and fine-tuned in a variety of simulation conditions. To test their
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, optimization, computational mechanics, and data-driven modeling of physical systems. Develop data-efficient computational methods for constructing predictive models from combinations of high-fidelity simulation