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Field
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ambitious investments in fundamental AI research. BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent
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ambitious investments in fundamental AI research. BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent
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Oden Institute for Computational Engineering and Sciences | Austin, Texas | United States | 3 months ago
development, including grant writing and academic presentation. Have access to the largest academic computing cluster in the world, including the largest GPU cluster. Application Materials Applicants should
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electromagnetic engineering problems. Programming experience in C/C++ and GPU is desired. Other qualifications being expected are as follows. Good analytical and problem-solving skills; Good analytical and
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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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institutional clusters. Write robust Linux bash scripts and job submission scripts for SLURM and PBS environments, including multi-node GPU/CPU workflows, monitoring, restart, and post-processing pipelines
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
(health insurance, paid leave, restaurant subsidy, etc.). Access to Inria’s computing infrastructure and to the ĀnandaBot project’s dedicated hardware (GPU servers, robot platforms). Integration in a well
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implementation for core capabilities such as distributed training and inference, workflow orchestration, GPU/accelerator utilization, model registries and artifact management, vector search and retrieval-augmented
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analyzing machine learning experiments; supporting scaled experiments involving neural networks, large language models, and GPU clusters; improving reproducibility, reliability, and usability of research
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research workflows. Maintain and evolve shared AI infrastructure including GPU-enabled workstations, AI development environments, and HPC resources used by students and researchers. Develop and maintain