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the development, analysis and assessment of policies that strengthen international regimes, collecting and analyzing data to identify trends and threats to the U.S. and international communities, developing and
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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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review of past field campaigns, through interactions with project stakeholders) Participate in summer field work Conduct observationally based research into the urban boundary layer using “big data” (e.g
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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 existing ones for scientific applications; (ii) Large Language Models (LLMs) and multi-modal Foundation Models (iii) Large vision-language models (VLM) and computer vision techniques; and (iv) techniques
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life – including the explosion of large language model (LLM) releases. BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications and uses
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experiment at the EIC. The program includes data analysis involving polarized targets at Jefferson Lab as well as full detector and physics simulations for ePIC. In addition, the candidate will collaborate
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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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industry, education, and public life – including the explosion of large language models (LLMs). BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications
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studies and computer simulations Collaborate with the BMAD development team at Cornell University by implementing new features into the code Participate in the EIC design effort in a more general sense