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together computer scientists, AI researchers, domain scientists, software engineers, and high-performance computing experts. You will help design and implement new methods for multimodal federated learning
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High Energy Physics Division, the successful candidate will contribute to the design, fabrication, and characterization of superconducting devices based on microstrip-coupled TES technology, with
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generation of closed-loop, AI-enabled experimental workflows that tightly integrate synthesis within situ and operando x-ray, electron, and optical characterization. The successful candidate will help bridge
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platform for X-ray absorption spectroscopy by integrating LLMs, scientific machine learning, physics-aware workflows, and strong computational chemistry/electronic-structure expertise. The researcher will
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in experimental physics and superconducting device development, with a focus on advancing multipixel single-photon camera technology and multiplexed readout for quantum information science applications
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information science and light–matter engineering, while engaging with CNM’s cleanroom and characterization capabilities, APS ultrafast and nanoprobe X-ray beamlines, MSD’s THz initiatives, and Q-NEXT’s national quantum
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We invite applications for a Postdoctoral Appointee position in the Chemical Sciences and Engineering Division (CSE) at Argonne National Laboratory. Working under the guidance of a supervisor, the
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time-resolved hard X-ray diffraction microscopy and spectroscopy on single-crystalline bulk and thin film quantum materials (e.g. ferroelectrics, multiferroics, strongly correlated electron systems
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, presentation of results at conferences, and production of peer-reviewed publications. Position Requirements PhD in chemical engineering, chemistry, electrochemistry, materials science, or a related field
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engineering, or related scientific background. Experience with electrochemistry, electrochemical analysis, and electrodeposition of metals, in contact with aqueous, non-aqueous, and molten salt electrolyte