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analyses. The work will involve network analysis, computational modeling, and simulation of control strategies for healthcare‑associated infections. Candidate profile: Applicants should hold a PhD in network
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simulated and measured results to assess quantities of interest. Interface with world-class exascale computing clusters. Work with a dynamic team of researchers, developers, experimentalists, and model
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systems. These models will be part of a multicellular modelling and simulation framework being developed as part of the Australian Research Council's (ARC) Discovery Project "Bridging biological boundaries
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of Environmental Engineering, ETH Zürich and matriculate in ETH Zürich. The research is related to development of experimental and modeling techniques to identify emission sources, simulate the airborne transport
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of manufactured parts, particularly in terms of geometrical accuracy, microstructural control, and mechanical performance. This PhD project aims to develop a Multiphysics model and simulation to gain in-depth
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simulations); developing and maintaining tools for data processing, visualisation of results and automation of computational experiments; optimising code performance and supporting the integration of models
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 22 days ago
/Description: The Miao Lab in the Computational Medicine Program and Department of Pharmacology at the University of North Carolina – Chapel Hill (https://www.med.unc.edu/pharm/directory/yinglong-miao/) is
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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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is of advantage: Knowledge of parallel programming and HPC architectures, including accelerators (e.g., GPUs) Experience in modelling and simulation, ideally in the field of energy systems Experience
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consequences on reactivity measurements during source transients; • Calculation of the sensitivity of the results obtained by simulation to data libraries, modeling choices, and technological uncertainties