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will involve designing beam dynamics experiments, measurement, simulation, and data analysis. This position resides in the Accelerator Physics Group in the Accelerator Science and Technology Section
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on designing system software for automating processes such as intelligent data ingestion, preservation of data/metadata relationships, and distributed optimization of machine learning workflows. Collaborating
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experiments to neutron reflectometry studies. The main objectives are: (1) To implement fluorescence microscopy techniques and Flicker spectroscopy to studies of DIBs under electrical stimulation; (2) Use other
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include data compression and reconstruction, data movement, data assimilation, surrogate model design, and machine learning algorithms. The position comes with a travel allowance and access to advanced
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) with questions related to this position. Major Duties/Responsibilities: Develop and apply machine learning models (ML) as surrogates for high-resolution process-based hydrologic models. Design and
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research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and developing foundational AI-driven techniques for the generation and exploration of complex, large
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-based systems Background in topology optimization and structural design Experience in thermomechanical characterization of polymer materials Demonstrated experimental capabilities and a strong
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domain experts—such as those in neutron scattering and urban science—to apply and evaluate research methods on large, domain-specific scientific datasets. Major Duties/Responsibilities: Designing and
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framework for driven and open quantum systems. Phenomenological modeling of dynamics/transport behaviors in complex systems, including strongly correlated electron systems. Experience in analyzing data from
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Computing (HPC) system architecture and intelligent storage design. The candidate will contribute to research and development efforts in scalable storage and memory architectures, telemetry-driven system