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://www.rc.ufl.edu/about/hipergator/ ), and the AI NVIDIA GPU SuperPOD (https://news.ufl.edu/2020/07/nvidia-partnership/ ) supporting UF’s campus-wide AI initiative (https://ai.ufl.edu ). These resources are available
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partners ML Systems & Infrastructure Design, build, and operate reproducible ML pipelines for training and inference (e.g., Snakemake or equivalent) including GPU/CPU scheduling, job queuing, and fault
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 3 months ago
, embeddings with transformers, training with flow matching) and high performance computing (e.g. handling large-scale parallel simulators, multi-node and GPU training on large supercomputers). When considering
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in the College of Engineering. UNLV GPU Cluster (named RebelX) is also available for A.I. research and education. GPU Cluster, supported by NSF MRI (#2117941), provides high-performance computing
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. Key Responsibilities: Develop and fine-tune computer-vision models, instance segmentation, and retrieval-based estimation from images and text metadata. Build and evaluate monocular depth pipelines and
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programme Reference Number AE2025-0510 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0510
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and optimize large-scale training and inference runs for foundation models on JUPITER (multi-GPU/node, mixed precision, parallelization, I/O optimization) Integrate multimodal data sources (e.g., scRNA
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24 Oct 2025 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Computer science Mathematics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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Arab Emirates Application Deadline 22 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 programme Is
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, managed directly by CARC staff, include multiple compute clusters that include state-of-the-art GPU resources, dedicated enterprise and high-performance storage systems, high-speed networking systems, and a