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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 goals of creating
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managing experiments using GPUs Ability to visualize experimental results and learning curves Effective inter-personal and team-building skills Self-motivated with an ability to work independently and in a
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animation tools, and GPU-based high-performance computing at MPI. You will also be embedded in a rich theoretical and computational environment supported by the Multimodal Language Department.Requirements
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datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress conditions. Implementing a multimodal approach for large-scale data analysis using CPU and GPU
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. Zou, which includes access to high performance computational resources with GPUs, conference travel support, and great opportunities for collaboration and networking with experts in Industrial
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or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design Previous collaboration with experimental biologists
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emphasis on programmability and the characterization of AI capabilities in CPUs, GPUs, and dedicated accelerators; Identification of computational patterns suited to AI-enhanced processors and standalone
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GPUs). Research Associate: Hold a PhD in high performance computing, computational fluid dynamics or a closely related discipline*, or equivalent research, industrial or commercial experience. Research
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well as access to the group dedicated computing cluster environment with H100, L40s, and A40 GPUs. This post is funded by the UKRI Future Leaders Fellowship, a flexible long-term public funding scheme
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optimizing PIC algorithms for modern heterogeneous architectures, including CPUs, GPUs, and other accelerators, the project seeks to achieve unprecedented efficiency and resolution in plasma simulations