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functional theory (DFT) are crucial computational tools to predict materials properties at the quantum level. In addition, electronic structure methods that go beyond the accuracy of DFT such as Quantum Monte
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matter theory that includes but is not limited to strongly correlated electron systems, high-temperature superconductivity, topological electronic states of matter, developments and applications of
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AI, or closed-loop materials discovery. Experience in computational heterogeneous catalysis, electrocatalysis, surface science, electronic-structure analysis, or alloy materials. Experience with high
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AI, or closed-loop materials discovery. Experience in computational heterogeneous catalysis, electrocatalysis, surface science, electronic-structure analysis, or alloy materials. Experience with high
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dynamics Develop machine learning potentials to predict SAM formation on solar cell absorber and battery electrode surfaces Understand the evolution of the electronic structure under realistic
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computational heterogeneous catalysis, electrocatalysis, surface science, electronic-structure analysis, or alloy materials. Experience with high-throughput density functional theory calculations
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the following: Attosecond electron/nonadiabatic quantum dynamics, ionization dynamics, methods to describe the electronic continuum, multireference electronic structure, tensor network states
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include: Ionization dynamics and photoelectron spectra Methods for describing the electronic continuum Multireference electronic structure Vibronic dynamics Selected relevant publications are
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impacts in the energy, agricultural, pharmaceutical, and transportation industries. Specifically, the ICC has dedicated research efforts in molecular and solid-state electronic structure theory
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limited to): biophysics, cold atom physics, electronic structure theory, hydrodynamics, machine learning, materials science, statistical physics, strongly correlated electrons, and quantum