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Field
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/bosonic systems, non-Gaussian states, multimode entanglement, or Wigner-function methods Experience with HPC workflows (cluster computing, GPU computing, reproducible pipelines) Track record
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projects Preferred: Experience with educational technology development and web programming LAMP stack design and implementation experience Knowledge of GPU and FPGA cluster management Experience with federal
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, accelerated partition utilizing next-generation GPUs—set to become available in 2027. Our vast array of professional development opportunities means you will grow and learn, having the chance to participate
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the ELLIS network of excellence in AI. You will be embedded in a vibrant, international team of PhD students and postdoctoral researchers, with access to substantial GPU compute, real robots and rich
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tuned for thermal transport and fire dynamics. FDS has been scaled up to 10,000 cores on Titan. The aim of this project is to improve code performance for serial, OpenMP, MPI, and potentially GPU
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• Access to modern computational infrastructure, including GPU clusters and supercomputers • Scientific freedom and excellent development opportunities • Salary according to the German public service pay
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the next generation of AI leaders, mentor students on groundbreaking research projects with access to state-of-the-art GPU hardware, forge partnerships with industry and academia, and contribute to AI
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sciences Collaboration with experts in lab science, medicine, and machine learning Modern GPU compute infrastructure A chance to contribute to cutting-edge research with real-world impact Who you are Strong
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responsible for AI/ML research infrastructure, including managing and optimizing on-premises GPU resources and AWS cloud services such as Bedrock and SageMaker. Responsibilities include deploying, monitoring
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such as quantum and analog computational models. You will explore how compilers, runtimes, and AI-driven agents can co-optimize complex architectures, reasoning across conventional processors (CPUs/GPUs