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on materials science tasks as well as integrate your semantic-AI services into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation Collaborate with
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different hardware backends. Design conventional (GPU-based) deep neural networks for comparison. Publish research articles, regular participation in top international conferences to present your work
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cardiology research with cutting-edge AI methods Top-Tier Mentorship: Collaborate with leading experts in AI, visualization, and medicine Compute Power: Access state-of-the-art GPU clusters and high
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, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs) to improve power efficiency and preserve power integrity. Integrated voltage regulators (IVRs
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) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution networks (PDNs
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(HPC) platforms used in machine learning, big data and artificial intelligence (AI) based applications (CPUs, GPUs, AI accelerators etc.) require high power demands with optimized power distribution
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, considering discrete modulation; Contribute to the implementation of digital signal processing algorithms in a FPGA platform; Contribute to the implementation of information reconciliation algorithms in a GPU
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, visiting researcher opportunities, access to modern GPU clusters for deep learning research, and strong academic-industry connections. CADIA's commitment to open science aligns perfectly with this project's
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into high-throughput GPU/HPC workflows, contributing to data management, metadata structuring, and semantic annotation Collaborate with experimentalists and theorists to validate extracted knowledge via in
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diffusion techniques to design materials with targeted optical properties, scaling to large systems through efficient representations and GPU parallelization. We will also create multi-fidelity predictive