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Field
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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 11 days ago
deployment, · knowledge of GPU computing and large-scale training, · experience working in an HPC environment, · experience with data annotation pipelines or synthetic data generation. We offer: · work in a
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of cores, and a growing GPU cluster containing thousands of high-end GPUs. Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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computing environments, and GPU programming. Necessary skills include knowledge of data processing using software (e.g., Matlab, R, IDL) and/or statistical/mathematical programming languages (e.g., R, Matlab
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | about 1 month ago
Behavior (CASCB), providing access to shared infrastructure, high-speed data networks, and central technical services. Computational needs will be met through multiple layers of resources: local GPU-equipped
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advanced compilation techniques for scientific and AI applications on heterogeneous GPU clusters. Research topics include scheduling, memory management, communication–computation overlap, and performance
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to diverse academic and industrial audiences. Proficiency in Python and deep learning frameworks such as PyTorch. Experience with Linux environments and GPU cluster management is essential. Competent in
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and GPU-accelerated tools for circuit and system design optimization, addressing challenges in physical design, timing analysis, and large-scale hardware design automation. The researcher will
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simulation methods, GPU-accelerated computations, several programming languages, and presenting results to wide technical and non-technical audiences. Additionally, the candidate will also develop theory and