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provides computational resources and has an interest group for AI that regularly meets, giving the successful applicant an opportunity to interact with a variety of NIST engineers and scientists. Smart
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energetics, thermodynamics, kinetics of protein-DNA interactions, and related phenomena, and connecting these measurements to organism fitness. Computation for engineering biology, such as RNA circuits, in
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to autonomously prepare and characterize liquid-formulations using neutron and X-ray scattering. Using this automated platform, we hope to explore the complex nature of molecular interactions that determine
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to address this by leveraging advances in integrated photonics, nonlinear optics and meta-photonics. This relies on advances in understanding nanoscale light-matter interactions, developing new materials
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(2020). Soubias, O. et al. Membrane surface recognition by the ASAP1 PH domain and consequences for interactions with the small GTPase Arf1. Sci Adv6, eabd1882 (2020). Binding (biochemical); Lipid
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are encouraged to submit research proposals on the following topics: DFT and MD for computational dielectric spectroscopy Properties of electrochemical double layer (effects on the local polarization, structure
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-based and data-driven prediction models are often impractical for operational use due to unrealistic assumptions, limited data availability, and prohibitive computational costs. To address
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, and speciation are fundamental to processes in biophysical systems and a wide range of industrial applications. All these processes share underlying changes in electrostatic interactions that require
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of prior physics knowledge into the data analysis, including both physics theory and databases of experimental and computational materials property data. We currently run 10 diverse autonomous platforms
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the weak interaction. Through measurements of its lifetime and beta-decay correlation coefficients, one can extract parameters that completely characterize the weak force. Measurement of the lifetime also