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supervisor, the successful candidate will conduct applied research on advanced battery materials using electrochemical, structural, and chemical characterization techniques. The appointee will support battery
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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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and structural behavior of these strategically important elements in geological materials. We are looking for a creative and driven experimental scientist with experience in synchrotron scattering and
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models for high-temperature structural materials with applications in nuclear reactors and other energy systems. The candidate will collaborate with ANL staff to review, validate, and enhance methods
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possible to visualize the interplay of soil structure and microbial life at scales bridging nanometers to millimeters, creating a unique opportunity to investigate how microbial communities are organized and
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to large single-crystal YIG spheres for optimizing magnon target mass and improving axion detector sensitivity. Develop detector sensing demonstration experiments for measuring the quantum efficiency and
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for multimodal federated learning that can integrate information across distributed datasets, including imaging, omics, clinical, text, sensor, and other structured or unstructured data modalities. Design and
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crystal growth and structure–property relationship discovery. The successful candidate will join a highly collaborative research environment that integrates robotic experimentation, advanced
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for Microelectronics” —a physics-informed AI framework that links composition, structure, and operating conditions to defect evolution and functional performance. The successful candidates will lead experimental
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phonons, magnons, and other emergent quasiparticles. The successful candidate will lead time-resolved X-ray diffraction experiments to reveal structural and electronic dynamics in condensed matter systems