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with a specific focus on fatigue (both high and low cycle) and fracture. Industrial relevance will be ensured by leveraging NIST’s partnerships with AM industry stakeholders, along with internal partners
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, 2016 , and Microphysiol Syst. 2020 Jun; 4: 10.21037/mps-19-8 ) that will make toxic metabolite detection more sensitive. Recent work includes a new, pumpless liver/heart system. NRC postdocs can propose
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RAP opportunity at National Institute of Standards and Technology NIST Mathematical Modeling of Magnetic Systems Location Information Technology Laboratory, Applied and Computational Mathematics
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for nondestructively characterizing AM alloys and identifying relationships between as-manufactured characteristics and in-service mechanical performance. Post-doctoral opportunities include research on linear and
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Robotic Systems for Smart Manufacturing Program is developing the measurement science needed to enable manufacturers to characterize and understand the performance of robotics systems within
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Laboratory with the Synchrotron Science Group and involve occasional travel to Gaithersburg, MD. The candidate would be responsible for planning and performing high-throughput XAS, XRF, and XRD measurements
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and related vulnerabilities. The research would involve applying tools and techniques from mathematical logic and software science to these challenging problems in software security and safety. Program
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velocity profile, unsteady flow) effect the performance of various flow meter types (e.g., turbine meters, critical venturis, ultrasonic flow meters), (3) development of theoretical models validated by
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unacceptably high. Today, firefighters largely rely on experience, training, and intuition to make time-critical decisions under extreme uncertainty, with limited real-time analytical support. Existing physics
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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