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seeking a postdoctoral appointee to join our team focused on designing the communication infrastructure for next-generation High-Performance Computing (HPC) and Artificial Intelligence (AI) systems
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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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discipline. Demonstrated hands-on experience and understanding of developing and applying HPC algorithms to sparse numerical, scientific and ML models. Demonstrated research experience with AI and ML
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
, large-scale AI, generative AI, and Exascale HPC to detect, quantify, and characterize key parameters of the global carbon cycle at high spatial resolution with a focus on above and below ground
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available codes and existing high performance computing (HPC) infrastructure Identify key physics of the systems through simulations to drive actionable design recommendations Identify gaps between existing
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-performance computing (HPC) environment Perform data analysis and visualization Perform machine learning and inverse design techniques Train and supervise masters and doctoral students Coordinate research with
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geologic media As for programming, we prefer familiarity with MATLAB, Python, and C++. Prior experience with high-performance computing (HPC) clusters and Unix operating systems is advantageous. We welcome
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computing (HPC) development of SeA (in collaboration with the DiStasio research group at Cornell University) and the broader QE package. We also expect this position to offer many other collaborative
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, Astronomy, or a closely related field is required. Experience with HPC systems, machine learning, and GRB monitor data analysis would be an advantage. Additional Information Applications must be submitted
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-house CFD software packages. (3) Designing and developing CFD sub-models for application to a broad range of CFD problems. (4) Using high-performance computing (HPC) to accelerate complex, large-scale