Sort by
Refine Your Search
-
RAP opportunity at National Institute of Standards and Technology NIST Mathematical Modeling of Magnetic Systems Location Information Technology Laboratory, Applied and Computational Mathematics
-
RAP opportunity at National Institute of Standards and Technology NIST N-Photon Entanglement and N-Photon Detection for Quantum-Based Metrology Location Physical Measurement Laboratory, Quantum
-
, forensics, statistics, and computer programming are applicable. key words Forensics; Forensic Science; Seized Drug; Opioids; Mass Spectrometry; Statistics; Analytical Chemistry Eligibility citizenship Open to
-
Metrology for Quasi-Optical Wireless Probing of Monolithic Microwave Integrated Circuits NIST only participates in the February and August reviews. Ultrafast electronic devices with fundamental operating frequencies above 100 GHz are used in a wide variety of applications—examples include radio...
-
RAP opportunity at National Institute of Standards and Technology NIST Multiplexed Assays for Cell-based Production of Biopharmaceuticals Location Material Measurement Laboratory, Biosystems and
-
RAP opportunity at National Institute of Standards and Technology NIST Lightweight Cryptography for Resource Constrained Applications Location Information Technology Laboratory, Computer
-
absorption fine structure), development of data-analysis approaches and computer software for simultaneous structural refinements using multiple types of data combined with ab initio theoretical modeling
-
://jarvis.nist.gov/) infrastructure uses a variety of methods such as density functional theory, graph neural networks, computer vision, classical force field, and natural language processing. We are currently
-
include the development of novel polymeric mechanical testing devices, novel adhesion blister testing devices, development of high-throughput screening devices, informatics, and data base development. key
-
; Autonomous; Machine learning; Informatics; High-throughput; Data mining; Functional materials; Active Learning