4 communication-network Fellowship positions at Lawrence Berkeley National Laboratory
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data. Communicate results through peer-reviewed publications, technical reports, conference presentations, and sponsor engagement. Build collaborative networks across Berkeley Lab and the DOE national
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materials or chemical modeling--e.g., graph neural networks, ML interatomic potentials, and uncertainty quantification. Strong programming skills in Python (or equivalent), with demonstrated experience in
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, edge resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific software. Publish and present results
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resources, and the DOE ESnet network. Develop and apply advanced workflow capabilities to improve performance, portability, and productivity of scientific software. Collaborate with computational and domain