29 structures-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM" positions at Argonne
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transient absorption and impulsive vibrational spectroscopy to correlate cavity-induced electronic, structural and spin-state changes with photophysical dynamics Position Requirements Recent or soon-to-be
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group in the division, comprising 11 Ph.D. scientists and approximately 7 postdoctoral researchers. The group conducts world-leading research in nuclear structure, nuclear astrophysics, fundamental
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harness the nonequilibrium correlation between structural, charge, and spin/pseudospin degrees of freedom in two-dimensional (2D) materials. The success of this program will lead to new means to control
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fabricate nanoscale electrical test structures (e.g., photolithography, e-beam lithography) Design, test, and characterize radiofrequency (RF) circuitry and measurement approaches Analyze and interpret data
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synchrotrons and x-ray free-electron lasers. Key Responsibilities Perform electronic-structure calculations using ab initio quantum chemistry methods and software (commonly CASSCF-based approaches) Investigate a
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: - Comprehensive understanding of applied computational materials science, including electronic structure methods and molecular dynamics. - Experience with High-Performance Computing (HPC) systems and intelligent
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critical thinking skills; intellectual curiosity. Able to structure and formulate solutions to complex problems. Highly motivated and detail oriented with the ability to work independently and in close
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and unravel structure-function relationships. This position is suited for a highly energetic and self-driven researcher willing to work in highly collaborative teams. This position will involve a
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/ML model development to design and discover redox-active materials with tunable properties (structure, charge state, etc.) Discovery of novel materials for energy storage and conversion and their
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models for composites of arbitrary structures to predict their homogenized properties. The candidate will also work closely with AI experts to develop workflows for composite structure discovery given