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the computational foundations of probabilistic programming, such as automatic differentiation, tensor libraries (PyTensor, JAX), gradient-based samplers, or model transpilation and compilation. Experience with
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating
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include the porting of lattice QCD libraries to the Exascale Architectures (e.g. Frontier at OLCF) and/or emerging programming models (HIP, SYCL, Kokkos, etc), software optimization and/or algorithmic
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. Conduct I/O and storage performance characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Collect, analyze, and leverage telemetry data from HPC systems
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, modern C++, and Linux-based development environments. Preferred Qualifications: Experience with point cloud processing and registration using libraries such Open3D or equivalent. Experience with LiDAR
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data acquisition, data analytics, statistical modeling, and machine learning in manufacturing environment. Proficiency in Python and common data science and machine learning libraries (e.g., NumPy
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. Conduct I/O and storage performance characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Collect, analyze, and leverage telemetry data from HPC systems
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characterization of HPC and scientific AI applications or libraries on multi-tier HPC storage systems. Design and evaluation of approaches for time-sensitive or data-intensive processing of data originating