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will collaborate closely with NSLS-II staff while developing cutting edge sample preparation and data analysis techniques that enable the next generation of the XCFS methodology. In addition
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a related field Experience with radiation transport codes (e.g., FLUKA, Geant4, MCNP etc.) Excellent programming and data analysis skills (e.g., Python, C++, or similar) Solid understanding
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complex terrain regions. CMAS does this by innovating on the fronts of meteorological data acquisition, analysis, and interpretation (https://www.bnl.gov/cmas/). The CMAS work portfolio is conducted within
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Information: Candidates must have received a Ph.D. by the commencement of employment. BNL policy requires that after obtaining their PhD, eligible candidates for research associate appointments may not exceed a
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artificial intelligence (AI) and machine learning (ML) methodologies and interested in advancing these tools for accelerating the analysis of the big data acquired by electron microscopy. • You work
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of gas chromatography coupled mass spectrometry or Liquid chromatography-mass spectrometry analysis. OTHER INFORMATION: Candidates should submit a CV, a brief description of how their research experience
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reflectivity, and IR spectroscopy. Other Information: This is a 2-year Postdoc Assignment. BNL policy requires that after obtaining a PhD, eligible candidates for research associate appointments may not exceed a
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data science Reporting the scientific results in academic papers and talks Required Knowledge, Skills, and Abilities: PhD. in Physics or related discipline. A good understanding of the physics of quantum
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-loss-spectroscopy is highly desirable. - Demonstrated quantitative data analysis abilities. - Effective communication skills. BNL policy requires that after obtaining a PhD, eligible candidates for
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.) and electrical device data analysis including transistor characteristics. You communicate effectively, verbally and in writing, evidenced by peer-reviewed publications and conference presentations