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Field
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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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CPU and GPU based HPC systems. Exploration of the capabilities of DPU/IPU SmartNICs to support network security isolation, platform level root-of-trust, and secure platform management/partitioning
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linear algebra computations, building software for scientific applications using GPUs (Graphics Processing Unit), multi-threading and parallelism, numerical discretization methods (finite differences
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(Xilinx Vitis/Vivado, Intel Quartus, HLS tools) HPC environments or GPU-accelerated computing On-detector firmware or data acquisition systems Familiarity with HEP data formats and reconstruction
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has access to a high-performance computational cluster dedicated to artificial intelligence research and developments using traditional multi-CPU systems, but also GPUs. Where to apply E-mail drimakat
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dynamics simulations using parallel computers or GPU computers. We correlate the obtained results with experimental data on polymeric functional materials to elucidate their dynamic behavior and clarify
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frameworks, e.g., Caffe, TensorFlow, PyTorch, and GPU-acceleration frameworks, e.g., CUDA will be a plus. Outstanding SW development and programming skills in C++, Python, ROS tools and libraries. Excellent
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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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-atmosphere dynamics. We will build an AI-enabled modeling system that couples a GPU-optimized ocean model with a biogeochemical module and AI-based, kilometer-scale atmospheric forecasts. This system will
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Microscopy Center. The project further benefits from excellent dedicated CPU and GPU computing infrastructure to support large-scale numerical modelling and data analysis. This is a full-time, two-year