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Field
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The Chemical Sciences and Engineering Division seeks a Postdoctoral Appointee to conduct research focused on the development of long-life, high-density cathode materials for electrochemical energy
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of Quantum Monte Carlo (QMCPACK, PYQMC) density functional theory (e.g. QE, VASP, PYSCF) and associated models to describe various properties of DOE-relevant quantum materials. The Materials Theory Group has a
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, and share data analysis pipelines for large-scale, high-density electrophysiological datasets, with a particular emphasis on sleep oscillations (including sharp wave-ripples, slow oscillations, and
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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stability, reduced leakage risks, and improved energy density. This project focuses on developing efficient materials and synthesis methods that can improve ionic conductivity, battery safety, cycle life, and
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density compared to state of the art. The selected candidate is responsible for conceptualization, design, and model-based optimization of the cell and will significantly contribute to the construction and
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complex magnets via interpretable machine-learning models, and develop improved AI models that can accelerate prediction of new synthesizable magnet candidates with high energy density and critical
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reports and presentations for group meetings. Key Responsibilities Conduct research to develop high-energy-density, long-life lithium–sulfur batteries using liquid and solid-state electrolytes Synthesize
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) and laser-based diagnostic techniques to characterize plasma properties, identify reactive species, and measure key plasma parameters, as well as the absolute densities of atoms and molecules
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also has ongoing projects examining the protective role of high-density lipoproteins in these biological pathways and processes, with the goal of developing novel lipoprotein-based therapies