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. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized
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Research program. The project aims to integrate a diverse suite of high-resolution observations (atmospheric, land surface, and infrastructure), diagnostic/predictive models, and civic engagement to provide
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based on two first-of-their-kind NION scanning transmission electron microscopes. In this postdoc position, you will be a member of the Electron Microscopy group and be mentored by scientists at CFN
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on diverse scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) development of novel machine learning models and adaptation
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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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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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and metabolic flux analysis. Knowledge and experience in Constraint-Based Modeling of metabolic networks. Experience in plant cultivation in growth chambers of green house space. Experience in the use
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scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) novel development of deep learning ML models and adaptation of existing ones
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novel genetic pathways regulating local and systemic acquired resistance, as well as growth-defense trade-offs. Using bacterial, fungal, and viral disease models, the research will focus on identifying
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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