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Field
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dedicated computing resources (3D visualization workstations, GPU servers). The research will be conducted in close collaboration with Philippe Nghe's team (Laboratory of Structural Cell Biology at École
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trajectory optimization, nonlinear programming, or genetic algorithms. High-performance computing (HPC), parallel numerical workflows, or GPU-accelerated model execution. Terms of Appointment This is a full
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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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have access to substantial AI compute, including in-house state-of-the-art H200 GPU servers, alongside further capacity through the Norwich Data Centre and access to national-scale AI compute through
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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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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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | 2 months ago
, operate, and scale HPC clusters and GPU resources to support computational biology, genomics, and machine learning workloads. Manage virtualization and containerization platforms (VMware, KVM, Docker
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projects, deploying workflows on large-scale computing environments, leveraging ORNL’s Frontier for its dense GPU-based high-performance computing resources to train large GeoAI models. Major Duties