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Posting Summary Logo Posting Number FAC00001PO26 Advertised Title Department Chair - Computer Science Engineering Campus Columbia College/Division College of Engineering and Computing Department CEC
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Programme? Not funded by a EU programme Reference Number 2025-2026_4_321 Is the Job related to staff position within a Research Infrastructure? No Offer Description Offer description: A three-year position as
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support the IIT High Performance Computing systems. The candidate will be the main system administrator of four HPC clusters with a total of about 360 GPUs. Within the team, your main responsibilities will
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for performance, cost-efficiency, and low-latency inference Develop distributed model training and inference architectures leveraging GPU-based compute resources Implement server-less and containerized solutions
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Technology (MHIT), and a PhD in Informatics. IIT faculty at the Cyberinfrastructure Lab (https://research.cec.sc.edu/cyberinfra/ ) are actively involved in applied research, and collaborate extensively with
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-access AI resources. Experience in GPU-accelerated computing and reproducible software development, including the use of containerization frameworks (e.g., Docker, Singularity) and collaborative code
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 2 months ago
GPU accelerated pipelines. In collaboration with a worldwide network of real-time data release and processing centers, the Data Access Engineer will take the alert distribution system to production
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The Computer Science program in the Computer, Electrical and Mathematical Sciences and Engineering Division (https://cemse.kaust.edu.sa ) at King Abdullah University of Science and Technology (KAUST
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, immersive, and interactive technologies. Highly proficient in real-time engines, AI-assisted tools, GPU-accelerated platforms, and emerging computational design workflows, you combine creativity with
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of computing systems—driven by edge devices, AI accelerators, and domain-specific architectures—has created unprecedented hardware heterogeneity. Modern platforms combine CPUs, GPUs, FPGAs, ASICs, and emerging