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planning and operations, and the interaction with other infrastructures. Some of these tools will require the development of underlying optimization methodologies and analytics frameworks. The successful
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, machine learning, and control in the energy sector. The postdoc researcher will perform theoretical study and algorithm development on optimization/control/data analytics methods and authorize peer-reviewed
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key element of the two-beam acceleration concept Emphasize Bayesian optimization approaches and integrate these methods into the facility control system Design, execute, and analyze accelerator
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optimization schemes. From developing AI models to uncover structure-function relationships with limited data sets, to building automated electrode-electrolyte interface discovery workflows and implementing full
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partners, and other national laboratories. Objective: Enhance THAPI: Extend and optimize the THAPI profiler (https://github.com/argonne-lcf/THAPI ) to concurrently profile AI/ML and ModSim components
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Deploy, commission, and operate TES X-ray microcalorimeter spectrometers at APS beamlines, including cryostat integration, beamline interfaces, alignment, and stability optimization. Perform pathfinding
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Mathematics, or a closely related field. Design and optimize multimodal LLMs to encode, fuse, and reason over heterogeneous scientific data from diverse modalities such as numerical tables, text, and images
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components. Work closely with a beam diagnostics physicist and controls group engineer to install and optimize diagnostic systems. Develop and integrate mmWave diagnostics equipment for beam position
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The Advanced Photon Source (APS) (https://www.aps.anl.gov/ ) at Argonne National Laboratory (Lemont, Illinois, US (near Chicago)) invites applicants for a postdoctoral position to build a physics
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include : Leading the physics design of a next-generation proton linac, optimizing acceleration efficiency and transverse focusing Designing new SRF accelerating cavity types across multiple operating