10 mobile-computing "https:" Postdoctoral positions at Lawrence Livermore National Laboratory
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investigate fault slip, stress evolution, and coupled mechanical, hydrologic, and thermal processes in geologic materials. Working with a multidisciplinary team, you will use high-performance computing and
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Scientific Computing (CASC) Division within the LLNL Computing Directorate. This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home
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. Develop reconstruction, simulation, and analysis software using modern C++, Python, ROOT, and HPC/Grid computing resources for processing multi-petabyte experimental datasets. Develop and apply state-of
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Description The Center for Applied Scientific Computing (CASC) within the Computing Directorate, is seeking a Postdoctoral Research Staff Member with a strong background in computational science, scientific
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, Crystal Plasticity) Ability to independently develop massively parallelized codes using C/C++/Python and proficiency in high-performance computing environments. Strong analytical and problem-solving
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Experience with FORTRAN, C/C++, and parallel computing. Experience in theoretical/computational studies of material microstructure evolution involving microelasticity and/or plasticity effects. Experience with
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Experience with FORTRAN, C/C++, and parallel computing. Experience in theoretical/computational studies of material microstructure evolution involving microelasticity and/or plasticity effects. Experience with
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property predictions (ranging from analytical to machine learning surrogate models) in LLNL’s Materials Acceleration Platform that is deployed on LLNL’s High Performance Computing infrastructure. Develop
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, theoretical, or computational work at LLNL, and will have access to LLNL's extensive computing facilities, talent pool, specialized laboratory facilities and field equipment. The HEDS Center at LLNL is
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competencies at LLNL. Fellows participate in experimental, computational, and/or theoretical work, and will have access to LLNL's extensive computing facilities, talent pool, specialized laboratory facilities