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Field
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research workflows. Maintain and evolve shared AI infrastructure including GPU-enabled workstations, AI development environments, and HPC resources used by students and researchers. Develop and maintain
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, and administers CPU/GPU HPC clusters, including management and compute nodes, storage infrastructure, interconnects such as InfiniBand, and physical infrastructure in the datacenter and related systems
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 3 months ago
HPC clusters and GPU resources to support computational biology, genomics, and machine learning workloads; Manage virtualization and containerization platforms (VMware, KVM, Docker, Apptainer
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automation tools (e.g., Ansible, PowerShell) and scripting languages. Strong understanding of CPU and GPU environments, network protocols, storage solutions, and cloud technologies. Knowledge of security best
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infrastructure--- including GPU-enable units and HPC server Manuscript and grant preparations --- for all research pertaining to mental health NLP and behavioral work. And to support grant administration, co
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technical support for research projects. Familiarity with shared memory and distributed memory parallelism (e.g., OpenMP, MPI, OpenACC), accelerators (e.g., GPUs), and large-scale file systems. Proven
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archiving solutions to collaboration and analytics tools. ARC also delivers Baskerville; a leading GPU accelerated National Compute Resource (NCR) and supports researchers using specialist regional and
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(including numerical optimisation, variational methods and MCMC sampling) C3 State-of-the-art deep learning (including transformers, graph neural networks and normalising flows) C4 Use of GPU programming and
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managing GPU-enabled infrastructure (NVIDIA GPUs, CUDA, multi-GPU systems) in cloud and/or on-prem environments. Familiarity with GPU orchestration in Kubernetes (e.g., NVIDIA device plugin, GPU scheduling
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support the operation and development of the Institute’s Linux-based compute infrastructure, including CPU and GPU clusters, storage systems, data centre hardware, networking interfaces, software