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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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reports, presentations, and other related media. Work in interdisciplinary collaborations with subject matter experts. Communicate research progress, challenges and achievements, and engage within and
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, and evaluate ML and NLP algorithms for scientific and security applications. Work in interdisciplinary collaborations with subject matter experts from a variety of domain sciences and security areas
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, foundation models, vision-language models, and computer vision for various problems relating to scientific discovery. Work in interdisciplinary collaborations with subject matter experts on various aspects
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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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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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. Implement, adapt, and evaluate ML and NLP algorithms for scientific and security applications. Work in interdisciplinary collaborations with subject matter experts from a variety of domain sciences 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
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process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request accommodation.