15 coding-"https:" "https:" "https:" "Inserm" Postdoctoral positions at Argonne in United States
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to develop and
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partners, and other national laboratories. Objective: Enhance THAPI: Extend and optimize the THAPI profiler (https://github.com/argonne-lcf/THAPI ) to concurrently profile AI/ML and ModSim components
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related field. Experience with finite element simulations and developing constitutive models. Knowledge of high temperature creep crack growth. Knowledge of engineering design codes such as the ASME Boiler
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interests Three letters of reference More details on the CPAC group can be found on our website: https://cpac.hep.anl.gov Completed applications will be reviewed as received, with all applications submitted
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encouraged. More details on the CPAC group can be found on our website: https://cpac.hep.anl.gov Applicants should send: Curriculum vitae Brief statement of research interests Qualified candidates will be
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of funds. Relevant Publications: 1. P. Chen et al ., Ultrafast photonic micro-systems to manipulate hard X-rays at 300 picoseconds, Nat Commun, 10:1158 (2019). https://doi.org/10.1038/s41467-019-09077-1 . 2
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to build a physics
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productivity across ideation, coding, experimentation, analysis, and writing. Interpreting results critically and positioning contributions within the broader research literature. Publishing research outcomes
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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis