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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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The Advanced Electron Microscopy and Nanostructured Materials Group within the Division of Condensed Matter Physics and Materials Science at Brookhaven National Laboratory invites applications
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FEM technique to quantitatively characterize amorphous materials, with high spatial and temporal resolution. • You will be part of a team performing experiments to lead the discovery of key physical
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computational resources for data analysis. This position offers a dynamic, collaborative environment, engaging with experts across plant biology, microbiology, structural biology, and computational sciences and
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the department on new potential collaborations. Position Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics
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. in computer science or a related field (e.g., engineering, applied mathematics, statistics) awarded within the last 5 years. Strong theoretical understanding and practical experience in deep learning
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at the Computational Science Initiative (CSI), within the Brookhaven National Laboratory. The selected candidate will collaborate on solving inverse problem, relevant for interference lithography process, by deploying
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Apply Now Job ID JR101857Date posted 06/16/2025 Scientists in Brookhaven’s Condensed Matter Physics and Materials Science Division (CMPMSD) study basic and applied aspects of quantum materials and
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investigators. Position Requirements Ph. D. in theoretical or physical chemistry, or a related field Extensive experience in one or more of the following areas: Computational modeling of homogeneous