Sort by
Refine Your Search
-
. The mechanisms by which cells transition from pluripotent to differentiated states is incompletely understood, and correlating measurable parameters to identify efficient culture conditions and release criteria
-
Laboratory, Software and Systems Division opportunity location 50.77.51.B7872 Gaithersburg, MD NIST only participates in the February and August reviews. Advisers name email phone Ram D. Sriram sriram@nist.gov
-
to understand dynamic changes within microbiomes or to design interventions (e.g., modeling algal blooms, improving human health or crop yields, bioremediation). This project seeks is to develop measurement
-
reviews. Nuclear magnetic resonance (NMR) spectroscopy has several important advantages for quantitative measurements of amount of substance: authentic material is not required for calibration, sample
-
@nist.gov 301.975.8993 Description Protein or peptide hormones control and regulate diverse physiological processes and are important targets in clinical labs for diagnosing disease. There is a need to
-
particles. These functional polyplex particles have numerous opportunities for the application of polymers in life science research.[1] There is much to learn concerning their mechanism of formation
-
properties such as electron-based spectroscopies, nanometer-scale imaging with energy filtering using a photoemission electron microscope (PEEM), and other optical measurements. Research is done in close
-
of the inflaton potential. Such experiments require even more precise measurement of the polarization of the microwave background with exquisite control of systematic errors. NIST is developing polarization
-
301.975.2282 Description In too many cases, the accuracy of measurements for nuclear forensics, nuclear medicine, high-energy physics, reactor engineering, and environmental monitoring is limited by the scant
-
been in development over the past 15+ years and their capabilities have grown significantly. An important effort within the LPBF community is the use of high-fidelity multiphysics models to predict melt