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technological platforms on site. The PhD student's work will be carried out at the IGBMC's integrative biology center. He/she will have privileged access to the team's computing server (GPU node) and the
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GPU clusters and high-performance computing facilities to accelerate your research. Good transport links in a central location with a free job ticket as a contribution to climate protection Low-cost
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degree in the above mentioned or related fields. What we offer State of the art on-site high performance/GPU compute facilities A team of 30+ expert colleagues A family friendly, green campus with on-site
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artificielle (IA) (CPU, GPU, accélérateurs d'IA, etc.) nécessitent une puissance élevée et des réseaux de distribution d'énergie (PDN) optimisés pour améliorer l'efficacité en puissance et préserver son
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scientific computing. You are proficient in several languages (Python, C/C++, or Fortran), with extensive knowledge in AI/ML and parallel programming (GPU, multi-threading, etc.). You have strong software
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and high flexibility in where and when you work. Access to HPC resources (including GPU clusters) at Helmholtz, the Leibniz Supercomputing Centre (LRZ), and the Forschungszentrum Jülich (FZJ). Training
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distributed computing for EMT simulations. • Experience with software development in Python, C++, or other programming languages. • Familiarity with GPU acceleration of numerical solvers, parallel sparse
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cardiology research with cutting-edge AI methods Top-Tier Mentorship: Collaborate with leading experts in AI, visualization, and medicine Compute Power: Access state-of-the-art GPU clusters and high
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on materials science tasks as well as integrate your semantic-AI services into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation Collaborate with
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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work