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Field
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program for AI Consultants. This position is within the OU Supercomputing Center for Education and Research (OSCER), a division of OU IT. Oversees research activities and provides operational supervision
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(R3) Country Morocco Application Deadline 21 Nov 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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the Computer Science program at New York University Abu Dhabi, seeks to recruit a research assistant to work on the intersection of compilers and deep learning. Many companies, such as Google, Facebook, and Amazon
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 2 months ago
Framework Programme? Not funded by a EU programme Reference Number 2025-09337 Is the Job related to staff position within a Research Infrastructure? No Offer Description The Makutu project team specializes in
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FLASH, Athena++, CASTRO, and other such tools are encouraged to apply. Exceptional candidates will bring demonstrated experience in programming and development in C++/Fortran as part of large multi
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data management plans with PIs and partners ML Systems & Infrastructure Design, build, and operate reproducible ML pipelines for training and inference (e.g., Snakemake or equivalent) including GPU/CPU
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when necessary. Work closely with ODFM to facilitate request for office and lab access. Manage any IT matters, including IT equipment allocation and support for GPU servers (if required). 2. Support on
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infrastructure, driving the design and evolution of HPC and AI platforms at scale. This role architects and implements next-generation GPU/CPU clusters, high-bandwidth InfiniBand and Ethernet fabrics, large-scale
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, ANGEL creates and deploys impactful green digital technologies for global sustainability. ANGEL’s mission aligns seamlessly with Singapore’s national objectives, such as the Singapore Green Plan 2030 and
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AI pipelines (similar to the attached prototype). Enable users to configure model parameters, connect modules, and monitor training progress. Display performance metrics (e.g., inference time, GPU