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the performance and scalability of large-scale molecular dynamics simulations (e.g. LAMMPS) using machine-learned potentials (e.g. MACE) through algorithmic improvements, code parallelization, performance analysis
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incorporating the molecular systems for strong light–matter coupling. The successful candidate will: Develop thin-film deposition and cavity fabrication processes, including spin coating, polymer matrix blending
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The Data Science and Learning Division (DSL) at Argonne National Laboratory is seeking a postdoctoral researcher to conduct cutting edge molecular and microbiology work to enhance non-proliferation
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modeling of x-ray spectroscopies sensitive to molecular chirality; simulations of x-ray–induced ultrafast electron-transfer, decay, and nuclear dynamics in gas- and liquid-phase systems; and the development
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: Proficiency in machine learning, statistical modeling, and quantitative methods for multi-omics data analysis Molecular Simulations: Expertise with molecular simulation tools like OpenMM, AMBER, Gromacs, and
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. Quantum Mechanical Calculations: - Performing first-principles based or Density Functional Theory (DFT) calculations for molecules/materials and interphases - Utilizing Molecular Dynamics (MD) simulations
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contribute to the Lab’s broader effort in conversion and separation of carbon-based materials. The role will require the individual to work with personnel that perform machine learning and molecular
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preservation (e.g., glycerol stocks, subculturing), aseptic technique, and operation under BSL-1 and BSL-2 containment requirements. Experience with microbial molecular biology techniques, including DNA/RNA
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application of ultrafast THz-pump and optical-probe techniques to detect narrow-band THz radiation and explore mode-selective dynamics in quantum and molecular systems. This work leverages state-of-the-art
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characterization with advanced computational chemistry tools, including molecular dynamics, density functional theory and Grand Canonical Monte Carlo simulations. Position Requirements A recent or soon-to-be