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, lead large-scale benchmarking across the full stack, and develop scalable classical simulations (e.g., tensor networks)—including performance bounds beyond brute-force classical simulability. This role
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scalability studies to identify and improve bottlenecks in large codes. Experience in development of data-driven reduced-order models in one or more of these areas: turbulence, boundary layer flows, combustion
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· The candidate will need to be in Pittsburgh, PA due to the large number of events and meetings on the CMU Pittsburgh campus and will need to travel to Washington, DC for meetings. Carnegie Mellon University is an
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within the U.S. Preferred Job Qualifications Experience using hierarchical statistical models, spatio-temporal models, machine learning, and developing data pipelines for large datasets. Experience with
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the validation of quantum computers operating in the classical-hardness regime. You will design and execute state-of-the-art experiments on superconducting quantum processors, lead large-scale benchmarking across
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running simulations or AI workflows on supercomputers Experience with training or applying large language models for research Experience with MPI and Input/Output (I/O), and data management Experience in
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simulations, design and conduct experiments, and analyze multimodal data streams in a continuous, real-time loop with minimal human intervention (https://www.nature.com/articles/s41524-024-01423-2 , https
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
Posting Information Posting Details Department UNC Inst for the Environment - 635200 Posting Open Date 10/30/2025 Application Deadline 12/29/2025 Open Until Filled No Position Type Postdoctoral
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, Greninger Lab Position Details Position Description The Greninger Lab at the University of Washington is seeking a Postdoctoral Scholar driven by curiosity, eager to dive deep, think big, and learn fast - a
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what are the impacts on individuals, households, markets, the agri-food system at large, and the environment? MIXTAPE will leverage existing national datasets (including remotely sensed data) and will