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Field
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fields, applying advanced techniques such as large-scale data processing and GPU-accelerated computing. Access to state-of-the-art research facilities and a new GPU cluster. Collaborative and inclusive
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part of the core PLI team, which includes top-tier faculty, research fellows, scientists, software engineers, postdocs, and graduate students. Fellows will have access to the AI Lab GPU cluster (300
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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++ Knowledge of GPU programming. Experience in application performance profiling. Desired qualifications: Experience from working on quantum computing Experience in FPGA development. Contract terms This postdoc
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Mathematics, or a related quantitative discipline. Strong programming skills in C++, Python, MATLAB, or similar languages; experience with GPU programming (e.g., CUDA) is highly desirable. Background in
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commonly used on Unix systems. Additional languages or experience with libraries for utilizing GPU hardware efficiently, e.g., CUDA, are a plus. Experience in AI programming with, e.g., PyTorch(-DDP
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physics, mathematics or any related field. What we offer State of the art on-site high performance/GPU compute facilities Competitive research in an inspiring, world-class environment A wide range of offers
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Deadline 2 Apr 2026 - 00:00 (UTC) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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made at the Postdoctoral Research Associate rank. The AI Postdoctoral Research Fellow will have access to the AI Lab GPU cluster (300 H100s). Candidates should have recently received or be about to
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-aware learning methods with domain decomposition techniques, enabling parallel training and efficient GPU-supported implementation. Your tasks: Development of physics-aware ML models for 3D blood-flow