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Field
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tactile skins, and a dedicated GPU cluster with eight NVIDIA H200 GPUs alongside access to ETH's central compute and the Alps supercomputer at CSCS A multidisciplinary team of mechanical engineers
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Process) Certifications/Licenses Required Knowledge, Skills, and Abilities Experience in GPU programming Experience working in interdisciplinary research teams Experience working with large and complex
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Karel. He's an AI agent we built, and he writes like a monk keeping vigil over a datacenter. Every morning Karel files a report: which pods are healthy, which GPUs sit idle, which tickets are aging, where
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resources, including Texas Advanced Computing Center (TACC), and multiple HPCs on campus, including some GPU-heavy clusters as well as the molecular biology, flow cytometry, and imaging equipment in the Life
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establish a research profile. Develop and execute innovative research projects. Develop, train, and evaluate modern machine-learning models on GPU/HPC infrastructure. Integrate AI methods with scientific
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team and supported by cutting-edge HPC and GPU infrastructure, you will contribute to internationally leading research, publish in high-impact journals and present your work at major scientific
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Programming Interfaces), high-performance computing cluster, Bash or GPU programming is preferred. When submitting your application, please list your programming experience, including your depth of knowledge
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architectures. Emphasis will be placed on heterogeneous computing and the optimal use of CPU and GPU resources to maximize model performance, scalability, and portability. A particular focus of the position will
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software (e.g., Paraview). Preferred Qualifications: Exposure to developing agentic workflows. Code development using Git repositories, GPU computing. Development of agentic workflows for scientific
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, Ansible, or similar technologies. Experience with Git-based development workflows, CI/CD, infrastructure-as-code, or modern DevOps practices. Experience designing infrastructure supporting HPC, AI/ML, GPU