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Argonne’s core values of impact, safety, respect, integrity, and teamwork Preferred Skills and Qualifications: Experience with high-performance computing and parallel computing Familiarity with data
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in GPU programming one or more parallel computing models, including SYCL, CUDA, HIP, or OpenMP Experience with scientific computing and software development on HPC systems Ability to conduct
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. Knowledge of multi-dimensional code development (in C++/C/Fortran) for two-phase/multiphase flow and turbulent combustion applications, and parallel scientific computing. Experience in geometry manipulation
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
: Expertise in rare event simulation, deep learning, and developing computationally efficient approaches for simulation and modeling in complex systems is highly desirable Experience with parallel computing
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development. Knowledge of parallel scientific computing. Ability to meet project needs and tight deadlines. Present and publish results in peer reviewed papers and/or journal articles. Skilled verbal and
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. Knowledge of C/C++ language and parallel programming with MPI. Background in modeling of engineering systems. Familiarity with high performance computing (HPC) software platforms is a plus. Skills in using
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and energy conversion systems. Knowledge of computational techniques and numerical methods. Knowledge of computer simulation and data analysis. Knowledge of C/C++ language and parallel programming with
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is preferred. Research experience in one or more of the following areas: 1.) Complex systems modeling, including simulation or analytical modeling, 2.) High performance computing, parallel programming