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have access to state-of-the-art facilities and major cyberinfrastructure investments, including the Advanced Research Computing Center (ARCC), the NCAR-Wyoming Supercomputing Center (NWSC), GPU computing
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. Training LLMs, large-scale deep learning systems, and/or large foundation models using GPU/TPU parallelization while setting up the environment/system network under various constraints, such as limited
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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place
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hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a given Tiramisu program, many code optimizations should be applied
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Engine, Unity, Blender, Adobe Creative Cloud, or DaVinci Resolve, with simple version-control tools like GitHub or Perforce. Experience with powerful PCs with strong GPUs, a mix of VR headsets like Meta
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for candidates with experience in ML model deployment, workflow orchestration, and high-throughput data processing, as well as experience working with large biological datasets in scalable GPU-based computing
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datasets in scalable GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and welfare benefits. A supportive team environment that promotes
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package, including health and life insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https
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datasets in scalable GPU-based computing environments. What we provide: A competitive compensation package, with comprehensive health and welfare benefits. A supportive team environment that promotes
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insurance, generous paid leave and retirement programs. To learn more about USC benefits, access the "Working at USC" section on the Applicant Portal at https://uscjobs.sc.edu. Position Description Advertised