95 assistant-professor-computer-science-data-"https:"-"https:"-"https:"-"https:" positions at Argonne
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. This position offers an exciting opportunity to contribute to fundamental and applied research in materials chemistry using advanced computational techniques and artificial intelligence. The project involves: 1
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, supply chain risk analysis, and data-driven modeling (including AI/ML where appropriate) to help inform decision-making for energy deployment and national competitiveness. In this role you will : Conduct
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computational research in accelerator science and technology. The focus is on developing and applying machine learning (ML) methods for accelerator operations and beam-dynamics optimization in advanced
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. The cosmology effort at Argonne includes staff members from the CPAC group, the Computational Science division, and the HEP Detector Group. The group also includes many postdocs, and a number of graduate and
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Physics, Materials Science, Chemistry, Chemical Engineering, Applied Physics, or a closely related field with a focus on computational materials modeling. Density Functional Theory (DFT) for surfaces and
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for electro-optic modeling Desirable Skills Data analysis using Python Experience with autonomous or AI-assisted synthesis workflows Familiarity with quantum transduction or quantum information science
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to ensure quality data. Communicate effectively with supervisors, peers, and Laboratory management through status updates, technical research reports, project presentations, and other regular channels
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related field Strong molecular biology skills (cloning, vector design, transformation), protein and nucleic acid prep-scale purification and analysis, and quantitative data analysis Excellent communication
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or equivalent in the scientific application of this knowledge and practical laboratory experience. Skill in devising and performing experiments to acquire identified data, using and maintaining research equipment
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The Materials Science Division (MSD) of Argonne National Laboratory is seeking applicants for a postdoctoral appointee in atomic layer deposition of thin films, in situ metrology, interface science