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behavior. You will combine density functional theory, thermodynamics, and automated Python-based workflows to generate physically grounded datasets describing oxidation states, defect formation, and surface
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environments. This project will focus on extending a Python-based workflow for compositional tuning and oxygen-vacancy formation in layered Li transition-metal oxides relevant to battery cathodes. The workflow
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. Strong experience developing, deploying, and optimizing applications and workflows in high-performance computing (HPC) environments. Demonstrated programming proficiency in C/C++ (preferred) and Python
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and data analysis, such as Python, Julia Ability to perform detailed simulations of the physical processes being studied. This includes the simulation of particle beams and their transport in complex
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, or a related field Ability to analyze complex multi-dimensional datasets Preferred Knowledge, Skills, and Abilities: Experience developing Python programs Experience with machine learning approaches
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)/machine learning (ML) applications in the power grid. * Experience with power system modeling, simulation, dynamics and/or optimization, phasor and electromagnetic transient (EMT)-based modeling, and Python