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Field
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ensure models can be deployed in large data real-world scenarios. Strong programming skills in Python, PyTorch, and/ or JAX are required, along with the ability to reason about neural network behavior from
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of the following technology areas: hardware/software co-design, performance optimization with heterogeneous and alternative computing systems (CPU/GPU/NPU/etc.), FPGA design, high-performance computing
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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
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with excellent facilities for protein science research. There will be direct access to advanced biophysical infrastructure in the biophysics core facility headed by the PI, a GPU cluster with working
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CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
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maintenance. Proficiency in programming languages such as Python, R, C#, and SQL. Familiarity with high-performance computing, cloud computing (e.g., AWS), GPUs, and DevOps tools, including version control
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, Computer Science, or a closely related field. Experience in at least one of the following areas: FPGA programming (VHDL/Verilog, HLS) Pixel detectors in high-energy physics or radiation detection
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’ experience post-Ph.D. Expertise in power systems and power electronics. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications
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machine learning techniques, and GPU programming. The simulation results will be compared to observational data obtained using facilities worldwide including ESO and NOT. Who we are looking for A successful
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to push the boundaries of what’s possible. We work with petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing thousands of high-end GPUs. We don’t