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academic setting Proficient in at least two programming languages used in research (e.g. Python, C++, Fortran) Experience with programming paradigms used in HPC (e.g., MPI, GPU-programming) Experience
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | about 2 months 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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learning and signal processing libraries; You have HPC/GPU computing experience, including running deep learning workloads on compute clusters (CUDA-compatible GPUs, multi-GPU training, Slurm). Your master's
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that combine parallel architectures (i.e., GPUs or accelerator boards, clusters) and numerical algorithms suited to such architectures with the goal of improving the speed of convergence and the stability
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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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detector plus Falcon 4i and the other with a Selectris energy filter and Falcon 4i. The Crick Institute has excellent High Performance Computing resources, dedicated high-speed data storage and CPU and GPU
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IT4Innovations National Supercomputing Center, VSB - Technical University of Ostrava | Czech | 28 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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agentic workflow (Llama, Claude, LangGraph, etc) Experience with training models on GPUs Experience working with Unix and/or Linux, including shell scripting Experience implementing NLP/AI algorithms and
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optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a
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research, research groups require access to high performance data storage for data-intensive processing, visualization for data analysis, GPUs, access to cloud services and research infrastructure skills