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Field
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++, Python, MPI, OpenMP, CUDA, OpenACC, etc.). • Excellent analytical, problem solving and decision-making skills • Creative and innovative individual with clear initiatives to improve lab operation • Flexible
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, Podman. Monitoring, Analytics and Visualization - Prometheus, Grafana, Elasticsearch, Checkmarx. Other leveraged technologies include, but are not limited to Slurm, MPI, CUDA, and Harbor depending
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experience writing software in C++ and Python, using libraries and technologies including CUDA, ROS, ROS 2, PyTorch, Docker and CI/CD tooling. You will be able to create and debug large software projects
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& Training, Network Programming (UDP/TCP/ZeroMQ), API Development, CUDA programming, python programming, Hardware Acceleration, strong verbal and written communication skills necessary for writing research
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, CUDA), numerical linear algebra, sparse matrix computation, and low-latency system design. · Machine Learning and AI Theory/Algorithm Design: optimization theory and algorithm design for deep learning
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engineering or digital twins. - Experience with scientific visualization tools and methods. - Experience with NVIDIA CUDA or GPU computing. - Experience with Docker or Kubernetes containerization and
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to gather requirements, manage expectations, and balance competing priorities. Experience supporting high-performance or GPU-enabled scientific computing environments, including NVIDIA/CUDA, performance
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, Kasm Workspaces, or similar technologies. Experience with GPU-enabled Linux workstations, NVIDIA/CUDA environments, scientific software stacks, or specialized research desktop environments. Exposure
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. Experience with performance tuning and benchmarking tools for HPC environments (e.g., Ganglia, Grafana, or similar). Experience with parallel programming frameworks (e.g., MPI, OpenMP, CUDA) and high
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schedulers such as Slurm, PBS, HTCondor, or LSF. Software development experience and familiarity with HPC programming environments such as C/C++, Fortran, CUDA, MPI, or OpenMP. Infrastructure and Automation