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Laboratory, Software and Systems Division opportunity location 50.77.51.C0391 Gaithersburg, MD NIST only participates in the February and August reviews. Advisers name email phone Ram D. Sriram [email protected]
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Advancing the state of the art in measurements of sound, vibration, force, acceleration and velocity
information into neural networks for modeling dynamic systems; use of uncertainty information to improve the performance of sensor-network based measurements employing machine learning; uncertainty
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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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, computer scientists, data scientists, and data engineers to define and implement community standards for knowledge representation and interchange. The successful applicant will conduct novel research in
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to dramatically improve both speed and energy efficiency compared to von Neumann architectures. The goal of this project is to develop new neuromorphic circuits, for example hardware based spiking neural networks
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wide range of experience with computational materials, software development, and/or additive manufacturing is welcome. [1] Toward a Standard Data Architecture for Additive Manufacturing, Li, S., Feng, S
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This project studies chiral assembly of chromophores at nanoscale by using chirality-defined single-wall carbon nanotubes (SWCNTs) as templates. New findings at NIST have established a general strategy to
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for fabricating near-net-shape metallic parts and generating microstructures that are infeasible with conventional metallurgy. However, the degree of commercial adoption of AM parts is impeded by
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nanocomposites containing these networks. Our objective is to develop metrologies to understand how morphology and functionalization affect the alternating current (AC) conductivity of composite materials
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technologies for microbial cells and mixtures. NIST is currently developing highly defined, single strain microbial cell materials and measuring them using a suite of cell enumeration and characterization