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Reconstruction Algorithms,” ICASSP 2015. (4) D.M. Pelt and J.A. Sethian, “A mixed-scale dense convolutional neural network for image analysis,” PNAS, January 8, 2019. If interested then, please, contact: Peter
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to acquire different kinds of images on large numbers of iPS cells in culture; machine learning algorithms and other image analysis strategies may be used to extract and test image features as predictors
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utilizes new techniques like First Order Reversal Curves (FORC) to characterize the distributions in these properties. A variety of experimental equipment is used, including superconducting quantum
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contribute for both targeted delivery and efficacy. To address problems associated with characterization and quantification of the drug load as they relate to efficacy, the ability to measure the distribution
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for measurement methods and applications of theory to adequately describe distributions of particles in complex fluid environments. Our goal will be to develop analytical ultracentrifugation methods
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for data sharing in single, distributed, or mobile environments as well as learn the limitations and practical approaches of their applications. The program will also research testing and verification
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@nist.gov 301.975.2105 Description Quantum communication, the distribution of entangled particles (usually photons), offers a fundamentally new physical resource for technological experimentation and
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; Electronic materials; Local structure; Nanometer scale; Pair-distribution function; Raman spectroscopy; Solid-state ionics; X-ray absorption spectroscopy; Citizenship: Open to U.S. citizens
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301.975.5251 Sushil K. Satija sushil.satija@nist.gov 301.975.5250 Description The structure of fuel cells, polyelectrolyte membranes, catalysts, and related materials, including the water distribution
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from a material surface. Neutron depth profiling (NDP) employs a cold-neutron beam from the NIST neutron source to nondestructively measure the depth distribution of nuclides of helium, lithium, boron