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on high performance computing systems or cloud infrastructure (including GPU-accelerated workloads). Practical experience with modern deep learning frameworks, model serving in production, and building end
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on GPU clusters and cloud HPC/ADK Implement data-efficient fine-tuning, adaptive learning workflows and agentic frameworks for reasoning Collaborate with machine learning experts and computational
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applied Machine Learning Hands-on experience with High Performance Computing Systems Basic knowledge of System Architecture of Supercomputers and NVidia-GPUs Practical experience with ML/DL workflows and
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their efforts on the education of students and the performance of life-changing research across a wide range of disciplines including medicine, engineering, physical sciences, energy, computer science, and social
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5 Dec 2025 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Sound engineering Researcher Profile First
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. Experience with graph-based data analysis or anomaly detection methods. Exposure to high-performance or GPU-based computing environments. Demonstrated ability to contribute to publications or technical reports
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and Memorial Sloan-Kettering Cancer Center, NY. Read more about the project here: https://health.medarbejdere.au.dk/en/display/artikel/supercomputer-and-ai-to-strengthen-danish-cancer-treatment-new
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, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
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computer hardware and network infrastructure for the ITS Research services. This covers the 12000 core, 100 GPU QM High Performance Compute cluster (see https://docs.hpc.qmul.ac.uk ), various hosted
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the College of Engineering. UNLV GPU Cluster (named RebelX) is also available for A.I. research and education. Detailed information about the CEEC Department can be found at: http://www.unlv.edu/ceec MINIMUM