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Knowledge, Skills, and Abilities: PhD in Chemistry, Physics, Biophysics, Biology, Biochemistry or Structural Biology. Proven ability to optimize peptide, protein or nucleic acid crystallization systems. Basic
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experience using and advancing data analytics and modeling, which may include using FEFF, Python or other modeling/programming languages. • Your experience is demonstrated through publications, GitHub
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microscopy beamlines at NSLS-II. In addition, the selected candidate will opportunities for collaborating with researchers at external facilities such as the Advanced Light Source of Lawrence Berkeley National
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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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proven ability to grow high quality single crystals, and ability to repair and maintain synthesis related equipment A proven ability to perform structural characterization with advanced transmission
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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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of proteins in disease. Our work helps to develop and apply novel tools in biochemistry, genetics, cell and structural biology, and bioimaging. We also leverage the unique capabilities of BNL’s National
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, structural biology, cell biology, and bioimaging. We also leverage the unique capabilities of Brookhaven’s National Synchrotron Light Source-II, Laboratory for Biomolecular Structure (LBMS) cryo-EM facility
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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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transport modeling and machine protection strategies for the EIC accelerator complex. This position will focus on Monte Carlo simulations to characterize the radiation environment resulting from beam losses