3 evolutionary-algorithm positions at Lawrence Berkeley National Laboratory in computer-science
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. Design, develop, test, benchmark, deploy, and tune agentic AI software frameworks and multi-fidelity optimization algorithms to close the feedback loop for automated scientific discovery. Deploy, optimize
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. Utilize machine-learning and data-mining approaches to recommend bioengineering interventions. Develop new machine-learning algorithms. Integrate machine learning techniques with mechanistic modeling
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to architectures, algorithms, and applications. Titled "Exploring Atomic Ensemble Qubits for Distributed Quantum Computing," this LBNL-funded initiative brings together experts from the ESnet, NERSC, and AMCR
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