18 machine-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at Argonne
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backscatter diffraction, focused ion beam specimen preparation, and computer vision or machine-learning analysis of microscopy datasets. The position requires strong experimental, analytical, written, oral
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, machine learning, and signal processing, as well as close collaboration with experts in computational science, electrical engineering, synchrotron physics, soil microbiology, and environmental chemistry
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machine learning (ML) to address future physics and detector challenges. Current physics interests include Standard Model measurements and searches for new phenomena. We welcome applicants who are
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applying artificial intelligence (AI) and machine learning (ML) methods for the autonomous, self-driving synthesis of nanoscale and quantum materials. This is an exciting opportunity to help shape a
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, including machine learning and Bayesian optimization approaches. Specific experience modeling the performance of advanced engineering ceramics and/or the high temperature performance of metal alloys
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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
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Engineering, Materials Science, or a closely related field Experience leveraging artificial intelligence or machine learning in the development of battery electrolytes and catalyst materials Demonstrated
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and Membrane Manufacturing group perform science-based membrane synthesis and scaleup development by using roll-to-roll manufacturing and machine learning enabled in-line characterization and quality