Los Alamos National Laboratory
Experimental Artificial Intelligence/ Machine Learning Scientist (Scientist 2)
Los Alamos National Laboratory, Los Alamos, New Mexico, us, 87545
Experimental Artificial Intelligence/ Machine Learning Scientist (Scientist 2)
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Experimental Artificial Intelligence/ Machine Learning Scientist (Scientist 2)
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Los Alamos National Laboratory The Center for Integrated Nanotechnologies (CINT) at Los Alamos National Laboratory (LANL) invites applications for a scientist position in Artificial Intelligence and Machine Learning (AI/ML) with a focus on experimental nanoscience. CINT is a Department of Energy Office of Science Nanoscale Science Research Center operated jointly by Los Alamos and Sandia National Laboratories. At LANL, CINT focuses on integrated and collaborative research at the intersection of nanoscience and technology, offering world-class facilities and a vibrant scientific community. Scientific thrusts in CINT include: Nanophotonics and Optical Nanomaterials; Quantum Materials Systems; Soft, Biological and Composite Nanomaterials; and In-Situ Characterization and Nanomechanics. We are seeking a highly motivated and innovative scientist to lead the integration of AI/ML with experimental nanoscience, supporting and advancing the needs of a dynamic, multidisciplinary user community. Responsibilities: Develop and lead an independent, high-impact research program in experimental AI/ML, aligned with the mission of CINT and LANL. Collaborate closely with experimentalists across disciplines to develop and apply AI/ML methods that accelerate discovery and deepen understanding in nanoscale science. Publish in high-impact journals and present research at national and international conferences. Engage with and support the CINT user community, helping to integrate AI/ML approaches into collaborative experimental projects. Requirements: Demonstrated expertise in AI/ML, especially as applied to experimental data or scientific instrumentation. Experience working with experimental platforms such as materials synthesis, microscopy, spectroscopy, or materials characterization tools. Experience in coding software for AI applications. Excellent communication and collaboration skills. Ability to obtain a Q clearance (which requires U.S. citizenship). Desired Qualifications: Ph.D. in physics, chemistry, materials science, computer science, engineering, theory, or a related field. Strong publication record in relevant areas. Experience with autonomous experimentation, data-driven materials discovery, or active learning in experimental settings. Demonstrated experience securing external funding or leading multidisciplinary research efforts. Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations.
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Join to apply for the
Experimental Artificial Intelligence/ Machine Learning Scientist (Scientist 2)
role at
Los Alamos National Laboratory The Center for Integrated Nanotechnologies (CINT) at Los Alamos National Laboratory (LANL) invites applications for a scientist position in Artificial Intelligence and Machine Learning (AI/ML) with a focus on experimental nanoscience. CINT is a Department of Energy Office of Science Nanoscale Science Research Center operated jointly by Los Alamos and Sandia National Laboratories. At LANL, CINT focuses on integrated and collaborative research at the intersection of nanoscience and technology, offering world-class facilities and a vibrant scientific community. Scientific thrusts in CINT include: Nanophotonics and Optical Nanomaterials; Quantum Materials Systems; Soft, Biological and Composite Nanomaterials; and In-Situ Characterization and Nanomechanics. We are seeking a highly motivated and innovative scientist to lead the integration of AI/ML with experimental nanoscience, supporting and advancing the needs of a dynamic, multidisciplinary user community. Responsibilities: Develop and lead an independent, high-impact research program in experimental AI/ML, aligned with the mission of CINT and LANL. Collaborate closely with experimentalists across disciplines to develop and apply AI/ML methods that accelerate discovery and deepen understanding in nanoscale science. Publish in high-impact journals and present research at national and international conferences. Engage with and support the CINT user community, helping to integrate AI/ML approaches into collaborative experimental projects. Requirements: Demonstrated expertise in AI/ML, especially as applied to experimental data or scientific instrumentation. Experience working with experimental platforms such as materials synthesis, microscopy, spectroscopy, or materials characterization tools. Experience in coding software for AI applications. Excellent communication and collaboration skills. Ability to obtain a Q clearance (which requires U.S. citizenship). Desired Qualifications: Ph.D. in physics, chemistry, materials science, computer science, engineering, theory, or a related field. Strong publication record in relevant areas. Experience with autonomous experimentation, data-driven materials discovery, or active learning in experimental settings. Demonstrated experience securing external funding or leading multidisciplinary research efforts. Los Alamos National Laboratory is an equal opportunity employer. All employment practices are based on qualification and merit, without regard to protected categories such as race, color, national origin, ancestry, religion, age, sex, gender identity, sexual orientation, marital status or spousal affiliation, physical or mental disability, medical conditions, pregnancy, status as a protected veteran, genetic information, or citizenship within the limits imposed by federal, state, and local laws and regulations.
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