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at least two related publications. Proficiency with core HPC programming languages and paradigms, including C/C++, Fortran, and MPI. Proficiency in GPU-accelerated HPC programming, with emphasis on CUDA and
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-field code, written in the Cuda C language and parallelized on a single GPU (Graphical Processor Unit). A parallelization on multiple GPUs would be a welcome development during the thesis. Where to apply
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Python, with experience in modern software development environments (Linux, Docker, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized
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contributions, and addressing bugs that arise as the platform is used in active research settings. The platform is built in C++ with CUDA-based computation running on NVIDIA GPUs, and is being developed both
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 1 month ago
biophysics/chemistry. Programming skills (e.g., bash scripting, python, Fortran, C++ and CUDA), expertise in computational modeling (such as Molecular Dynamics, virtual screening, free energy calculations and
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at the Secret level or higher and may be subject to a government background investigation to upgrade clearance eligibility, if required Preferred skills/experience areas include: Python, C++, CUDA, time-series
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. Ubuntu) is essential.. Knowledge of GPU computing, CUDA programming, model optimization, and industry experience in engineering software development would be an advantage. Excellent written and oral
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potential use of Rust, CUDA, C/C++, Bash/Zsh, and Haskell while collaborating closely with students, professionals, and external partners. The role offers significant opportunities to contribute to system
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Language Model (LLM) GPU cluster to ensure stable and reliable operation of training tasks; (b) handle GPU node failures, IB network anomalies, CUDA/NCCL errors and Kubernetes scheduling failures, perform
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programming (C++, MPI, CUDA/HIP/ROCm). Preferred Qualifications: Familiarity with LLVM/MLIR development and multi‑language IR ecosystems. Background in formal methods or automated reasoning. Experience with