309 web-programmer-developer-"https:"-"UCL"-"https:"-"https:"-"PhD-Jobs" positions at NIST
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(e.g., thermogravimetric analysis, differential scanning calorimetry, and dynamic mechanical analysis, etc.), (5) developing mechanical test methods for samples (at small and structural-level scales
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using novel analytical approaches. Specifically, this research will focus on (1) development of laboratory methods to produce controlled-size micro- and nanoplastics; (2) development of field-flow
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. This problem becomes even more pressing for simultaneous multi-qubit operations. The goal of this project is to develop software tools for the automated tuning of high-fidelity readout and gates in silicon spin
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development of RF MEMS/NEMS resonators. Several resonator geometries are being developed that combine low-loss mechanical design, unique materials, and electrostatic, electrothermal, and piezoelectric actuation
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evolution. The Group aims to advance fundamental understanding, improve predictability for design, ensure reproducibility and comparability, and facilitate scalability for real-world applications
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. In this project, we are developing metrology needed for the synthesis, processing, and characterization of low-dimensional materials to enable reliable nanoscale device development and manufacturing
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Tytus Dehinn Mui Mak tytus.mak@nist.gov 202.360.6799 Description In the past decade, the rapid pace of development in mass spectrometry technologies has accelerated the rise of metabolomics and resulted
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@nist.gov 301.975.2860 Description New developments in detector technology have made possible the acquisition of the full electron scattering distribution at each pixel in a scanning transmission electron
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are not sufficiently accurate, or the methods are too expensive to accurately model sufficiently large systems. As a result, these computational problems are ideal for developing machine-learned potentials
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parameter space challenging due to the sheer number of possible compositions. To enable rational design of these materials, we have developed a highly adaptable sample environment that can be programmed