Opportunity at National Institute of Standards and Technology NIST
Machine learning on facility-scale data and autonomous electron microscopy
Material Measurement Laboratory, Office of Data and Informatics
||Gaithersburg, MD 20899
Please note: This Agency only participates in the February and August reviews.
|June W Lau
The NIST Electron Microscopy Nexus is an internal shared-use facility with 13 electron microscopes (S/TEM, SEM, dual-beam instruments), and our data infrastructure is set up so that all microscopy datasets from all users are collected and archived at a central file location. In 2020, we have begun curating and labeling microscopy datasets using NexusLIMS (DOI: 10.1017/S1431927621000222 ), which makes programmatic querying of labeled data possible through the app’s REST API.
Datasets include (but not limited to): 1D spectroscopy (EDS, EELS, CL), 2D images and diffraction, 3D to 4D hyperspectral/multimodal and 4D-STEM images. Dynamic (temporally-resolved) images recorded from our stroboscopic microscope (DOI: 10.1063/1.5131758 ), ETEM (Gatan K2 camera), and FIB instruments. The materials investigated with these microscopes spans all non-biologic materials classes.
The Nexus facility and its rapidly maturing data ecosystem is unique in the world. With this production system, we are looking to augment our ability to rapidly answer science questions using the aggregated data volume. Additionally, we seek to develop and deploy new autonomous measurement platforms using present and next generation electron microscopes. If you are a creative individual and can imagine what “can be” given the data richness of our program, we invite you to apply and share your ideas with us.
AI, machine learning, electron microscopy, autonomous experimentation
Open to U.S. citizens
Open to Postdoctoral applicants