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- Delft University of Technology (TU Delft); 16 Oct ’25 published
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on GPU clusters and cloud HPC/ADK Implement data-efficient fine-tuning, adaptive learning workflows and agentic frameworks for reasoning Collaborate with machine learning experts and computational
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, OpenCV), GPU computing (e.g., CUDA), SLAM and point cloud processing (e.g., PCL). Familiarity with ROS-based development and Linux software tools is considered a fundamental asset. (30
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suitable for part-time employment. Starting date: 17.10.2025 Job description: Design, develop and apply an flexible and integrative multiscale FWI using GPU-accelerated spectral-element simulations (Salvus
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working in interdisciplinary teams Clear record of communicating original results in writing and presentations Desired Qualifications: Knowledge of GPU architecture and experience programming GPUs
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. Ability to succeed in an interdisciplinary team and communicate results clearly in writing and presentations. Desired Qualifications: Knowledge of GPU architecture and GPU programming. Interest
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algebra methods targeting large-scale HPC systems. Optimization of linear algebra libraries for modern architectures (e.g., GPUs). Exploration of linear algebra methods in computational physics applications
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Python, using GPUs), with the precise balance determined by the candidate’s background and interests. The mathematical tools involved will include matrix analysis, optimization, backward error analysis
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infrastructure, driving the design and evolution of HPC and AI platforms at scale. This role architects and implements next-generation GPU/CPU clusters, high-bandwidth InfiniBand and Ethernet fabrics, large-scale
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Inria, the French national research institute for the digital sciences | Pau, Aquitaine | France | about 1 month ago
coupling with adaptive meshes. High-order spectral finite element methods (SFEM) offer superior accuracy per degree of freedom and are naturally suited to HPC architectures (CPU/GPU clusters). Two main
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these codes in C++ or Fortran Adopting these codes for multiple-CPU and/or GPU platforms via parallelization schemes. Validating these codes via canonical and real-world examples. Job Requirements: PhD in