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Field
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science, conversational AI, and marketing analytics and on substantial investments in on-premises GPU infrastructure that allows us to work with confidential partner data under full data control. The focus
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computing and GPU infrastructure for the development and evaluation of LLM-, VLM-, and agentic AI solutions Research across the entire automotive software development lifecycle, from requirements and software
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benchmark them with a realistic case study. The main focus of the project can develop either more in the mathematical theory of MCMC, the implementation of code for the Jülich supercomputers (GPU/CPU
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compute (CPU/GPU), high-speed interconnects, storage and parallel file systems, cluster management, and user-facing platform services. In practice, the Senior HPC Architect drives end-to-end technical
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Research Computing to architect advanced computing, GPU-enabled environments and serve as a specialized partner to researchers to develop AI/ML research workflows within UAB Research Computing. In
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streams with perturbation signatures and fit these. For these fits, we will explore the speed up from using GPUs as well as machine learning techniques, e.g. simulation-based inference. Finally, we will use
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programming languages. Experience with DICOM data, medical-image registration, high-performance computing, or GPU-based computation. Familiarity with machine-learning or deep-learning methods for medical-image
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 5 days ago
management, or storage integration * Databases, data platforms, distributed systems, GPU-enabled computing, or MLOps workflows * Experience providing technical leadership, mentoring developers, or owning major
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environments, Slurm/Slinky workloads, Kubernetes/OKE services, Open OnDemand, GPU and CPU partitions, and shared storage. Help provision, configure, scale, and validate compute, storage, networking, and platform
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. Demonstrated experience with training and calibrating other large-scale complex models. Demonstrated ability to pretrain large-scale models from scratch, including distributed multi-GPU training. Demonstrated