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(e.g. weather, hydrology). Expertise in data and model parallelisms for distributed training on large GPU-based machines is essential. Candidates with experience using diffusion-based or other generative
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systems, including GPU-accelerated platforms. Develop and maintain scientific software, primarily in Python, using modern practices for software development, testing, documentation, and version control
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 13 days ago
group. Our offer Computing The department operates Urania, a high-performance cluster with ~6,050 cores; Hypatia, a high-throughput cluster with ~12,000 cores; and two GPU servers, Saraswati and Lakshmi
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laser arrays Optimization and acceleration of existing simulation codes Parallel computing and high-performance computing (HPC) GPU acceleration, where appropriate Development of scalable numerical
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specialized for studies of presolar grains and ancient planetary materials. ASIAA has a dedicated CPU cluster, several GPU servers, as well as access to the National High-performance Computing Center. ASIAA is
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Dask and NetCDF or Zarr datasets. Experience with GPU or distributed training and familiarity with agricultural or environmental applications of weather forecasts. Experience working in interdisciplinary
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extracting transport properties from molecular dynamics trajectories. ● Experience with GPU-accelerated machine learning frameworks (for example CUDA, PyTorch, or GPU-enabled LAMMPS). ● Experience
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— shortest paths, connectivity, clustering, or graph traversal on GPU clusters and distributed-memory systems. Sparse direct and iterative linear solvers — communication-avoiding methods, sparse LU
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), including 504 NVIDIA Blackwell B200 GPUs. These resources are provisioned directly through the group's institutional allocation. The University of Florida is the state's flagship land-grant, Carnegie R1, and
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strategies to port multi-dimensional integrodifferential equations, describing higher order scattering/correlations to specialist large scale GPU hardware. Carry out independent research, work closely with