178 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at NIST
Sort by
Refine Your Search
-
301.975.5508 Description Quantum information technologies have exploded in recent years, but eventual fault tolerance and networking requires the exchange of quantum information between quantum processing
-
metabolomics. Our studies focus on developing new mass spectral data analysis algorithms (e.g., clustering) to better solve the common key persistent problems arising from factors such as mass shift and peak
-
, or techniques that will speed up analysis times, provide increased information to the chemist, and/or simplify data interpretation while enhancing data quality. One of the goals of the forensic program at NIST is
-
and novel data-processing tools need to be developed to embrace these new techniques and further elevate their capabilities. Instrumentation available for this research includes ion trap, Orbitrap, and
-
the development of analytical methodologies, from both instrumentation and informatics standpoints, for the multifaceted and convoluted data that are obtained from complex biological, chemical, and forensic samples
-
also measure nonspecular scattering, from which we can derive in-plane information. Systems of interest include polymer films, magnetic thin films and multilayered structures (using polarized beams
-
, and complete products of combustion) will be performed. Comprehensive data sets of this type have not been previously reported for full-scale enclosure fires. The chemical data will be augmented by
-
involving an actual or planned nuclear attack. Conclusions drawn from this collected data coupled with law enforcement and intelligence information may support attribution—the identification of those
-
property data are available for only a few dozen fluids. A better understanding of fundamental fluid behavior would allow the accurate prediction of properties for those fluids lacking good data and thus
-
shocks and stressors). This research effort relies extensively on modeling and optimization, with consideration for field data collection, and statistical and geospatial data analysis. Informed by