44 machine-learning-"https:" "https:" "https:" "https:" positions at Brookhaven National Laboratory in United States
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time associated with family planning, military service, illness or other life-changing events. At Brookhaven National Laboratory we believe that a comprehensive employee benefits program is an important
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salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans
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automates building and modifying surface structures, submitting DFT calculations, post-processing electronic structure and vacancy energies, and extracting machine-learning descriptors for modeling oxygen
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of relevant work experience as a post-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events. Brookhaven National Laboratory
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-doc and/or in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events. At Brookhaven National Laboratory we believe that a comprehensive
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in an R&D position, excluding time associated with family planning, military service, illness or other life-changing events. At Brookhaven National Laboratory we believe that a comprehensive employee
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Brookhaven Site Office (BHSO). Support Contractor Assurance and the Laboratory's Enterprise Risk Management process. Promote operational excellence and foster a learning and improvement culture. Additional
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University. BSA salutes our veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities
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veterans and active military members with careers that leverage the skills and unique experience they gained while serving our country, learn more at BNL | Opportunities for Veterans at Brookhaven National
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approaches for using machine learning to analyze X-ray data, particularly Resonant Inelastic X-ray Scattering (RIXS). The position will collaborate with experts in RIXS experiments (Mark Dean), computational