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ensemble structures. As an Empire AI-funded fellow, you will have early access to the Empire AI clusters, utilizing state-of-the-art GPU architectures to push the boundaries of structural biology. This
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The subject is only described in English. B2/C1 level of English
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Ryzen CPU, GPU, and NPU, in terms of inference speed, energy consumption, accuracy, and performance per watt. Different quantization levels (e.g., int8, fp16) will also be explored. Develop intelligent
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studies. These pipelines must be capable of efficiently exploiting different types of parallelism, both at the level of a computing node (CPU and GPU) and at the level of a cluster of PCs. This environment
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distinction for three consecutive periods (2014-2018 and 2018-2022 and 2023-2026). ICN2 comprises 20 Research Groups and 8 Research Support Units and Facilities, covering different areas of nanoscience and
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May 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 the Job
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, Cloud Service Deployment). Desired: Experience with High-Performance Computing or GPU programming (CUDA). Specialized knowledge of Neural Rendering (NeRF/3DGS) or Satellite Photogrammetry. Demonstrated
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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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domain-specific support to researchers working in artificial intelligence, machine learning, and data analytics. Enable researchers from different disciplines to apply appropriate machine learning and data
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optimized code written by expert programmers and can target different hardware architectures (multicore, GPUs, FPGAs, and distributed machines). In order to have the best performance (fastest execution) for a