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monitor Slurm-based training and evaluation jobs Debug failures related to distributed execution, checkpointing, filesystem performance, networking, and GPU utilisation Help maintain reproducible
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, improve, and use high-performance simulation tools for dynamic rupture, including GPU-oriented numerical methods You will verify and validate the numerical methods against benchmark problems and
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) Distributed systems concepts, APIs, scalability, observability, identity and access management, and security AI/ML platforms and supporting infrastructure services HPC systems, GPU clusters, and
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experimental and clinical MR systems fully dedicated to research, state-of-the-art local and scalable cloud-based compute infrastructure (CPU, GPU) and workshops for mechanical, electrical and
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frameworks, RAG pipelines, PyTorch, HuggingFace) and with model optimization and efficient inference. Experience with GPU computing and high-performance or distributed computing environments. Exposure
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understanding of TCP/IP networking, routing and firewalls Nice to have Hands-on experience with HPC technologies such as InfiniBand networks and multi-GPU systems Experience deploying or operating Lustre or
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prototyping (S-Gym), single-GPU workstations (M-Gym), and multi-node HPC at the National Supercomputing Centre Singapore (L-Gym). The Gym's purpose is to close the gap between high-dimensional
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shared scientific instruments (e.g., electron microscopy, X-ray imaging, and light microscopy). It supports researchers across three compute scales: laptop-based prototyping (S-Gym), single-GPU
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and ML environments such as UCX, NVLINK, InfiniBand, UltraEthernet and related networking frameworks. Evaluate and optimise the communication library and associated software components on GPU clusters