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with job schedulers, e.g. SLURM, PBS, SGE, etc. ● Experience working at an academic institution ● Experience with parallel codes and libraries (e.g. MPI, OpenMP, Cuda) ● Experience with research and/or
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using the shared memory and message passing techniques. Knowledge of OpenMP and MPI or similar programming directives and libraries. Knowledge of GPU programming with CUDA, HIP, oneAPI or OpenMP for GPUs
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using the shared memory and message passing techniques. Knowledge of OpenMP and MPI or similar programming directives and libraries. Knowledge of GPU programming with CUDA, HIP, oneAPI or OpenMP for GPUs
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mathematics, e.g., probability theory, linear algebra, differential/integral calculus Prior programming experience in Python is a must, C++ and CUDA experience are a plus Hands-on experience in working with
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 12 hours ago
). Experience and proficiency across the software development lifecycle (version control, documentation, and testing) is required. Experience with GPU acceleration frameworks (Nvidia CUDA, PyCUDA, CuPy
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scripting methods (i.e. Python, MATLAB, C++, CUDA, Bash, and/or SQL) and machine learning / deep learning methods Active learning, exploration, optimal experiment design, Bayesian optimization, reinforcement
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and train CNN and SNN models utilizing frameworks such as Keras, PyTorch, and SNNtorch Implement GPU acceleration through CUDA to enable efficient neural network training Apply hardware-aware design
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and domains. Ability to troubleshoot connectivity issues and familiarity with vulnerability management and patching processes. Python and nVidia CUDA modules setup and configuration. Relational database
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research related software, Python, R, Matlab, Mathworks, Julia, Ansys, Intel, nVidia cuda and GCC compilers. Experience with dev ops tools such as GitHub, GitLab, Ansible, package management tools for rpm
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techniques and probability theory ● GPU Programming: Experience with GPU programming and optimization for ML models, utilizing frameworks, like CUDA or OpenCL ● Experience with applied computer vision, such as