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Field
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or OpenMP. Experience in heterogeneous programming (i.e., GPU programming) and/or developing, debugging, and profiling massively parallel codes. Experience with using high performance computing (HPC
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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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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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. Demonstrated experience developing and running computational tools for high-performance computing environment, including distributed parallelism for GPUs. Demonstrated experience in common scientific programming
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transformer architectures (e.g., ViT/TimeSformer, CLIP/BLIP or similar) in PyTorch, including scalable training on GPUs and reproducible experimentation. Demonstrated experience building explainable models (e.g
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responsibility for our unique GPU-accelerated 3D FDTD software suite and extending its capabilities Modelling the effects of atmospheric turbulence fields Software development (3D modelling and coding in Python, C
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://hpcdocs.hpc.arizona.edu/) resources including access to CPU and GPU hardware. Additional access to HPC resources at leadership compute facilities will be readily available to the successful candidate as part of external
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leading-edge scientific challenges and needs. The NanoSIMS lab is specialized for studies of presolar grains and ancient planetary materials. ASIAA has a dedicated CPU cluster, several GPU servers, as
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challenges and needs. The NanoSIMS lab is specialized for studies of presolar grains and ancient planetary materials. ASIAA has a dedicated CPU cluster, several GPU servers, as well as access to the National
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computational fluid dynamics (DNS, LES, or RANS) and/or high-performance computing (MPI, GPU, or parallel solvers), as demonstrated by application materials. Evidence of peer-reviewed publications in fluid