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) Proficiency in programming languages such as Python or C++ Experience with AI frameworks like PyTorch or TensorFlow Strong communication skills and ability to work in a team environment Ability to model
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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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Postdoctoral Appointee - Uncertainty Quantification and Modeling of Large-Scale Dynamics in Networks
Knowledge in modeling and algorithms for large-scale ordinary differential equations (ODEs) and differential-algebraic equations (DAEs) Proficiency in a scientific programming language (e.g., C, C++, Fortran
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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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relevant numerical methods to dramatically reduce time to a feasible solution, parallelization of computations/high-performance computing, and other emerging and novel techniques to improve the efficiency
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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