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; while they are trained using GPU-based optimization methods, the actual information processing takes place without a GPU, making them energy-efficient and fast. Diffractive networks are to be designed
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collaborative workspace. Additional information about the department and its facilities can be found at https://aerospace.illinois.edu/ . Our faculty and students are affiliated with and have access to
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programming skills in Python and familiarity with modern ML tooling and reproducible research practices Experience training and deploying machine-learning models on GPU-based systems; familiarity with HPC
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, including custom shader development (e.g., CG, GLSL) and adaptation across different graphics backends Experience with performance engineering for mobile, AR, or MR platforms, including GPU/CPU profiling
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, conducting experiments on GPU servers, analyzing results, and maintaining reproducible research pipelines. The candidate will routinely review recent literature, participate in weekly research meetings, and
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experimentation. Familiarity with distributed or accelerated computing environments (e.g., GPU-enabled systems, shared compute clusters ). Working knowledge of database systems, including: Relational databases (e.g
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computing, or hardware reliability. Experience with GPU, FPGA, embedded, or specialized AI accelerator platforms. Experience with scientific programming, benchmarking, or reproducible experimentation
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-dessous. La plateforme ExaNBody [1] développée au CEA est dédiée à la mise en place de simulation à N-Corps dans un contexte de Calcul Haute Performance (CPU/GPU). Elle est notamment utilisée par le
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<span lang="en">Universitätsklinikum Hamburg-Eppendorf</span> | Hamburg, Hamburg | Germany | 11 days ago
resources for travel and conferences
- Work on cutting-edge AI methods with direct clinical relevance
- Access to large-scale multimodal biomedical datasets and modern GPU infrastructure
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, containerisation, version control and service deployment on HPC systems or cloud infrastructure, including GPU-accelerated workloads Experience with deep learning frameworks, production model serving