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and other complex fluids using molecular simulations. In order to make these simulations more computationally feasible, development of coarse-grained models and new Monte Carlo or molecular dynamics
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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proceed with the definitionand numerical implementation of the models for the simulation of the magnetic, electrical, thermal, and mechanical behavior of these devices. Appropriate experimental setups will
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fields in cosmic voids and filaments. The candidate will reduce model uncertainties by producing new large cosmological simulations of the magnetic outputs from galaxies in the ENZO code, which will test
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photogrammetric data Design procedural modeling frameworks for district- and campus-scale built environments Produce interoperable assets (e.g., 3D Tiles, glTF, FBX) supporting downstream simulation platforms
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in power electronics systems and components, Multi-physics modeling using open-source simulation environments (e.g. FastFieldSolvers, Elmer, PyPEEC, MEEP), Circuit simulation using open-source tools
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The »Grid-free Methods« department at the Fraunhofer Institute for Industrial Mathematics ITWM focuses on the modeling and efficient simulation of complex industrial problems for the design and
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). Knowledge of complex network modelling, omics data analysis or computational simulation. Research FieldOther Internal Application form(s) needed Perfil. .pdf English (606.79 KB - PDF) Download Additional
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intelligence models, and visual analytics tools that integrate urban data, forestry data, temporal and multivariate network modelling, and simulation of infection dynamics in Swedish city environments
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to demonstrate knowledge of computational epidemiology, individua lbased simulation, spatial modeling of epidemics and other geospatial software. * Ability to show proficiency in data management. * Ability