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systems. This work will specifically focus on combining ML algorithms with classical data analysis and control techniques to develop robust in situ (i.e., in real-time, during the operating experiment
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of applicatioins and phenomena including quantum information processing, quantum simulation, and quantum metrology. Our group is part of the Joint Quantum Institute and we have research on both
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) for streaming data from the PMTs or other detectors, two independent DFB laser systems, numerous broadband electro-optic modulators, a two Mach-Zehnder waveguide based I/Q modulator for fast and precise frequency
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relates to manufacturability and basic cell functions. Advanced automation systems will also be employed to generate control samples with varying degrees of cell health to serve as training data
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. However, detailed analysis of biologics is quite limited using these approaches. In contrast, nuclear magnetic resonance (NMR) is a high resolution and information-rich technique that is highly sensitive
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data analysis aspects of these multi-component soft matter therapeutic formulations. The binding between polyphosphazenes and proteins are visualized by cryogenic electron microscopy (cryoEM), therefore
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of liquid samples as a function of temperature, composition, and concentration. These measurements can yield information on the polarization dynamics of different conformations in DNA nanomachines and protein
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angela.hightwalker@nist.gov 301.975.2155 Description Photonic and magnetic nanoparticles have shown great potential in a wide range of applications such as catalysis, information storage, energy, and medicine. Our
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. The postdoc will develop machine learning algorithms to analyze phenotype and sequence data, as well as active learning algorithms to optimize and control experiments in directed evolution. This position
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NIST only participates in the February and August reviews. The modern transmission electron microscope (TEM) is capable of atomic-resolution structural and chemical imaging. However, such data