45 machine-learning "https:" "https:" "https:" "https:" "UCL" "UCL" positions at Brookhaven National Laboratory
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, United States of America [map ] Subject Area: Computational Science / Artificial Intelligence/Machine Learning Appl Deadline: (posted 2025/11/19, listed until 2026/01/26) Position Description: Apply Position Description
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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
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skills Preferred Knowledge, Skills, and Abilities: * Knowledge of both the theoretical fundamentals and applications of machine learning. * Experience working in multidisciplinary collaborations. * Strong
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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