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San Francisco and Berkeley Lab Team Up on Pioneering Climate Study

April 27, 2022

Berkeley Lab computational resources are helping the City and County of San Francisco adapt to the Bay Area's changing climate and the extreme storms it is expected to bring. Read More »

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Osni Marques Takes on New Role with Exascale Computing Project

April 26, 2022

Osni Marques, a staff scientist in the Applied Math and Computational Research Division, has been tapped to lead the Training & Productivity effort within the Exascale Computing Project. Read More »

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Computational Analysis Enables Breakthrough in Biomolecular Dynamics

April 20, 2022

A new study with data analyses from Berkeley Lab computational researchers helps broaden the physical understanding of biomolecular assembly. Read More »

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CCSE’s Hannah Klion Selected for 2022 Rising Stars

April 19, 2022

Hannah Klion, a postdoctoral researcher in the Center for Computational Sciences and Engineering, has been selected to be part of this year's Rising Stars conference. Read More »

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Lindsay Bassman Awarded Prestigious Marie Curie Fellowship

April 12, 2022

AMCR’s Lindsay Bassman has been awarded one of Europe’s most competitive and prestigious postdoctoral fellowships — the Marie Skłodowska-Curie Actions — to continue her work in quantum thermodynamics. Read More »

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Advancing New Battery Design with Deep Learning

April 4, 2022

A team of researchers from Berkeley Lab and UC Irvine has developed deep-learning algorithms designed to automate the quality control and assessment of new battery designs for electric cars. Read More »

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Michael Mahoney Tapped to Lead the Machine Learning and Analytics Group

March 29, 2022

Berkeley Lab’s Scientific Data Division recently appointed Michael Mahoney to lead its Machine Learning and Analytics Group. Read More »

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Berkeley Lab Computing Resources Enable Deeper Understanding of Supernovae Explosions

March 23, 2022

An international research team recently made history by recording the earliest post-explosion detection of a Type Ia supernova, using cosmological models developed at Berkeley Lab and supercomputing resources at NERSC. Read More »

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HYPPO: Leveraging Prediction Uncertainty to Optimize Deep Learning Models for Science

March 1, 2022

With a growing need for optimization tools that can enhance deep learning models and their training to improve predictive capabilities and accelerate time-consuming computer simulations, a Berkeley Lab team developed HYPPO, an open-source software tool for hyperparameter optimization of deep neural networks. Read More »

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Open Sourced Control Hardware for Quantum Computers

February 24, 2022

To make engineering quantum hardware more accessible, the Advance Quantum Testbed has open-sourced a new electronics control and measurement system for superconducting quantum processors. Read More »