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to ensure high-quality data. Communicate results through peer-reviewed publications, technical reports, conference presentations, and sponsor engagement. Build collaborative networks across Berkeley Lab and
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targeting NERSC HPC resources, edge resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific software. Publish
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workflows targeting NERSC HPC resources, edge resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific
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techniques in materials or chemical modeling—e.g., graph neural networks, ML interatomic potentials, and uncertainty quantification. Strong programming skills in Python (or equivalent), with demonstrated
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, genomics, and other scientific domains. Hopper Fellows concentrate on the development and optimization of scientific and engineering applications leveraging high-speed network capability provided by