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Field
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resources. Working knowledge of NVIDIA-specific technologies relevant to research computing, such as GPU-enabled workflows, CUDA-enabled tools, GPU resource use, or AI/ML computing environments. Basic
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will be viewed highly favorably. Experience with GPU acceleration or code parallelization paradigms (e.g., MPI, OpenMP, CUDA). FLSA Exempt Full Time/Part Time Full Time Number of Hours Worked per Week 40
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(e.g., MPI, OpenMP, CUDA, VASP, Gaussian, and Nextflow, Open OnDemand) Experience with the installation, configuration and administration of Docker and Singularity Experience with the installation
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Python, ML, and AI for chemical applications Preferred: Familiarity with HPC systems Proven track record of research in ML/AI for chemistry Strong coding foundation (Python) Knowledge of C++ and CUDA
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documentation practices. Experience with GPU-accelerated hardware platforms and software engineering including NVIDIA GPUs and CuPy/CUDA/C++ programming. Familiarity with 5G/6G wireless standards and AI/ML
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Knowledge, Skills, and Abilities This is a high-level software development position that requires proficiency in object-oriented programming (particularly python and C++, and GPU programming, e.g., cuda) and
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(Python, Bash, Perl) and scientific computing (MPI, OpenMP, CUDA). Experience with configuration management tools (Ansible, Puppet). Familiarity with container technologies (Docker, Singularity, Kubernetes
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, Rosetta, etc.). Experience working in High-Performance Computing (HPC) environments (Slurm, CUDA execution) or cloud infrastructure (AWS/GCP) optimized for multi-GPU training. Familiarity with
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for multi-core processors, with particular emphasis on the CUDA platform, which enables the use of graphics processing units (GPUs) for general-purpose tasks, history of application for external financing
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(e.g., vLLM, NVIDIA CUDA environments, Blackwell/ARM64 hardware). Experience with Microsoft Copilot, Microsoft 365 automation, or Power Platform infrastructure. Proficiency in scripting or programming