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PhD (within the last 0-5 years) in field of physics, chemistry, materials science, electrical engineering, or a related field Demonstrated expertise in electronic structure theory Experience with large
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Recent or soon-to-be-completed PhD (within the last 0-5 years) Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Job Family Postdoctoral Job Profile Postdoctoral
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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks an outstanding postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials
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machine learning models at a world-class high-performance computing facility The candidate will have access to state-of-the-art computing resources, including: NVIDIA DGX-2 Systems: Powerful platforms
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ultrafast nonlinear optical spectroscopy techniques—such as transient absorption and impulsive vibrational spectroscopy—the role aims to probe polariton-controlled electronic and nuclear dynamics occurring
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scientific experiments at APS beamlines, which will define the baseline for the usage of the TES X-ray microcalorimeter spectrometers. Collaborate with detector, electronics, and beamline staff to integrate
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. The ability to characterize products using electron microscopy, XRD, zeta potential, dynamic light scattering, GC-MS, FTIR, NMR, EPR. Experience in interdisciplinary collaborative research. Job Family
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relationships in next-generation electronic materials. This role involves creating AI models for real-time data analysis, enabling autonomous experiments through active learning and "curiosity-driven" exploration
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electron beams, advanced beam-manipulation for precise electron-beam shaping, and ML for accelerator science. Responsibilities Develop and deploy ML algorithms for autonomous operations and optimization
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discovery. Requirements: - A PhD in materials science or related science or engineering field received within the past 0-5 years. - Excellent written and oral communication skills as well as the ability