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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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candidates working in formal methods and/or computer systems with interests in one or more of the following areas: machine-checked verification of systems software, GPU kernel semantics and verification, and
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Max Planck Institute for Gravitational Physics, Potsdam-Golm | Potsdam, Brandenburg | Germany | 11 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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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | 4 days ago
, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the above-mentioned fields. What we offer State-of-the-art on-site high performance/GPU compute facilities
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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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applications for scientific, agricultural, environmental, geospatial, or cyber-physical systems. Experience with GPU computing, distributed training or inference, high-performance computing systems, cloud-native
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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