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The Center for Nanoscale Materials (CNM) at Argonne National Laboratory seeks an outstanding postdoctoral researcher to advance data-driven, physics-informed AI for microelectronics materials
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in high-impact venues Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in field of High Energy Physics or Nuclear Physics, or a closely related discipline
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in theoretical physics or a related field (Completed prior to the start date of the postdoctoral position and no more than 5 years
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monitoring and gradient tests. Participate in training opportunities, including attending the US Particle Accelerator School (USPAS). Position Requirements PhD completed in the past 5 years or soon to complete
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. Position Requirements A formal education in Physics, Materials Science, Chemistry, or a related field at the PhD level with zero to five years of employment experience. Demonstrated experience with high
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. The researcher will develop and apply physical, chemical, and electrochemical models for advanced battery technologies and associated manufacturing processes. This work will quantify and explain relationships
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, superconducting nanowire particle detectors and pixelized MCP-PMTs. Position Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in experimental nuclear or particle physics or a related
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Requirements Recent or soon-to-be-completed PhD (within the last 0-5 years) in physics or a closely related field Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork
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candidate would be a PhD in geophysical sciences, computer science, or machine learning with experience in developing and verifying deep learning-based models for large dynamical systems (e.g. weather
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(CFD) to develop and optimize new processes and equipment designs using high-performance computing Develop process- and facility-scale models as the foundation for digital twins of chemical processing