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Field
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and hundreds million) Skills in AI-enabled and GPU-based calculations are welcome Good communication skills and the ability to work in a team environment Ability to work independently to solve critical
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computing pipelines and large-scale GPU resources, to scale LLM development and deployment. Your profile PhD in machine learning, computer science, computational biology, computational neuroscience
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appropriate use of GPU resources. Digital cultural heritage: OCR and HTR, enrichment of historical and multimodal collections, and applied studio courses delivered with GLAM partners. This list describes
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Tech. ARC currently operates compute resources comprised of • 50,000+ CPU cores • 500+ GPUs • over 10 PB of storage • a world class immersive visualization lab. We continuously evaluate emerging research
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solutions on modern HPC and GPU-accelerated systems. This role includes supporting climate and geophysical science applications, enabling large-scale AI training and inference workflows, and contributing
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research. What about computing power? Well, BOLD also has access to national compute resources (3M GPU hours on Isambard for the first 1.5 years) and we are working hard to get to 5000 H100 equivalent
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Training and optimizing ML algorithms on GPU hardware architectures, specifically NVIDIA based Working with geo-spatial data Statistics, multivariable calculus, and linear algebra Exploratory data analysis
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preferred). Familiarity with CUDA toolchains and building GPU-enabled software. Experience with automation/configuration management tools (e.g., Ansible, Puppet, or similar). Experience developing tools
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managing systems utilizing GPU (NVIDIA and AMD) clusters for AI/ML and/or image processing. Knowledge of networking fundamentals including TCP/IP, traffic analysis, common protocols, and network diagnostics
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, and validated through simulation and experiments. For experiments, IDLab-UAntwerp's world-class research infrastructure, including GPU Lab, Software Defined Radios and programmable beamformers, as