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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 21 days ago
with turbulence, flow control, scientific computing, or data-driven modeling. Experience with GPU computing and supercomputers is desirable. Good English skills. Additional information The position is
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frameworks (PyTorch, TensorFlow). Experience with dataset curation, annotation workflows, FAISS/embedding retrieval, LLM-based parsing, RAG-style pipeline, and GPU/HPC training. Familiarity with 3D data
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for Computer Graphics and Real-Time Rendering. By using ANNs, coded for high-performance on cross-vendor GPUs, we aim to create new techniques for global illumination and material models. The subject works with
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infrastructure, model training, and inference systems. You'll design, develop, and optimize scalable data pipelines and build multi-node GPU training and inference pipelines for foundational models. You'll also
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strategies for large-scale or streaming data. Develop parallelized and GPU-accelerated learning modules, ensuring scalability and performance efficiency. Build and maintain robust data pipelines for high
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, Vehicular Communications Experience in system modeling and simulation of communication systems Strong programming skills in MATLAB are required; experience with Python, C/C++, or GPU-based computing is an
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of predicting electronic, structural, and thermal quantities while leveraging underlying symmetries for computational efficiency. There will be a significant computational component in deploying multi-GPU codes
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algorithms as well as deep learning workflows on GPU servers (use of Git, Docker, and PyTorch) Design, implementation, and evaluation of spatial proteomics and multiplex analyses for characterizing the tumor
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. Preferred Qualifications : * Experience in programming on modern computing platforms including x86 and ARM-based CPUs and accelerators such as NVIDIA or AMD GPUs. * Experience working in an academic research
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. Duties: Develop and execute a strategic roadmap for research computing infrastructure, including GPU-enabled high-performance computing (HPC) environments and enterprise storage systems including