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Field
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will design, implement, and validate novel algorithms, and benchmark them against state-of-the-art reconstruction pipelines. Strong programming skills (e.g., Python/C++ and GPU-based computing) and
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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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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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environments Experience with parallel computing environments, HPC in a Linux environment Experience with surrogate modeling Experience with data analytics techniques Familiarity with C++ and GPU programming
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environments Experience with parallel computing environments, HPC in a Linux environment Experience with surrogate modeling Experience with data analytics techniques Familiarity with C++ and GPU programming
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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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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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capabilities. We can access a high-performance computer cluster with the most advanced GPU resources. We also partner with the New York Proton Center, which houses one cyclotron, three rotational gantry
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, cybersecurity, software and hardware accelerators such Data Plane Development Kit (DPDK), eBPF, SmartNICs, P4 programmable switches, and GPUs. Situated in USC’s Engineering and Technology Innovation Center