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for incomplete or inaccurate data and communicate with landowners to rectify inconsistencies Input grazing management data into large project level databases and calculate grazing management metrics that will be
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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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make a difference in the world! Position Information The selected candidate would assist a team of ecosystem modeling scientists to perform process-based ecosystem models based research and develop
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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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, 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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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
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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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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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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