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for Computer Graphics and Real-Time Rendering. By using ANNs, coded for high-performance on cross-vendor GPUs, we aim to create new techniques for global illumination and material models. The subject works with
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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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strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high
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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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community. We provide the resources to match your ambition: Industrial-Scale Computing: Exclusive access to massive GPU clusters and high-performance computing. Guaranteed Talent Pipeline: Generous
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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
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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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-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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. Duties: Develop and execute a strategic roadmap for research computing infrastructure, including GPU-enabled high-performance computing (HPC) environments and enterprise storage systems including