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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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to perform quantitative spectroscopic analysis using monochromated EELS or other advanced spectroscopy techniques Preferred Knowledge, Skills, and Abilities (one or more of the following): Background in
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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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., EBL, physical vapor deposition, ALD etc.) and critical dimension (CD) measurements & analysis using scanning electron microscopy (SEM) and CD analysis software. You communicate effectively, verbally and
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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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.) and electrical device data analysis including transistor characteristics. You communicate effectively, verbally and in writing, evidenced by peer-reviewed publications and conference presentations
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, enhanced by machine-learning and data-driven analysis techniques. Additionally, the study will encompass electrically triggered events that mimic the voltage-based signaling of biological synapses
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with colleagues focused on other experimental and theoretical techniques Demonstrated data analysis skills for complex multi-dimensional data Preferred Knowledge, Skills, and Abilities: Experience in
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colleagues focused on other experimental and theoretical techniques Strong data analysis skills such programing language such as Python Preferred Knowledge, Skills, and Abilities: Experience in spectroscopic