373 embedded-system "https:" "https:" "https:" "https:" "UCL" "UCL" positions at NIST in United States
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NIST only participates in the February and August reviews. The Communications Technology Laboratories (CTL) at NIST is looking for a postdoctoral fellow to work to develop high-throughput materials
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integrated devices architectures, such as three-dimensional integrated circuits (3D-ICs), are poised to open up new avenues for more powerful functionally diverse electronics devices. Unfortunately, there is a
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Microscopic and Spectroscopic Characterization in Engineered Polymeric Materials NIST only participates in the February and August reviews. The purpose of this research is to develop advanced
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NIST only participates in the February and August reviews. As of today, there is a plethora of cyber-physical instruments consisting of physical sensing (e.g., microscopy imaging) and cyber (digital
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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 sriram@nist.gov
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variability that is due to experimental conditions in metabolomics experiments. The aim of this project is to establish a standard protocol to evaluate the analytical variability associated with liquid
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of emerging devices. The ultimate goal is to explore the landscape of emerging hardware-based artificial intelligence systems to better understand the role played by measurement and metrology in these complex
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ionization sources that allow for single-drop analysis with minimal competitive ionization and maximal analyte intensity is of major interest. Additionally, creation of statistical treatment methods
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Bergonzo christina.bergonzo@nist.gov (240)314 6333 John P. Marino john.marino@nist.gov 240.314.6361 Description There has been a recent emergence of RNA biotherapeutics; that is, small RNAs used as drug
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DeCost brian.decost@nist.gov 301.975.5160 Description Trustability and physical interpretability are critical requirements for the development of robust and sustainable machine learning systems needed