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Field
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and collaborative team of computational scientists, software and AI engineers, and neuroscientists, you’ll have access to high-performance workstations, CPU/GPU clusters, and experimental systems
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, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized knowledge of Neural Rendering (NeRF/3DGS) or Satellite Photogrammetry. Demonstrated
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, enhanced sampling, QM/MM) Experience improving performance and scalability of simulation workflows via: Parallelization and performance engineering GPU/accelerator optimization Algorithmic innovation
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infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi-node GPU training and inference pipelines for foundational models. You'll also
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. Preferred Qualifications : * Experience in programming on modern computing platforms including x86 and ARM-based CPUs and accelerators such as NVIDIA or AMD GPUs. * Experience working in an academic research
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simulation software related to radiation transport and computational fluid dynamics for multithreaded CPU and GPU computing platforms. Conduct performance profiling of existing scientific software, identify
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. Duties: Develop and execute a strategic roadmap for research computing infrastructure, including GPU-enabled high-performance computing (HPC) environments and enterprise storage systems including
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-based CPUs and accelerators such as NVIDIA or AMD GPUs. ● Experience working in an academic research computing center or large-scale HPC environment. ● Experience with GPU computing and
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Python, with experience in modern software development environments (Linux, Docker, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized
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using Cinema 4D within a motion graphics or interactive media pipeline. Experience with GPU-based rendering tools such as Octane Renderer for creating high-quality visualizations, motion graphics, or 3D