Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Information Technology Laboratory

Statistical Engineering Division

How to Work With Us

For the most up-to-date information on current opportunities, please contact Julia Sharp (julia.sharp [at] nist.gov (julia[dot]sharp[at]nist[dot]gov)).

NIST/NRC Postdoctoral Associateship Program

NIST, in collaboration with the National Research Council (NRC), conducts several national competitions each year to identify outstanding scientists and engineers at the postdoctoral level for two-year research appointments at the NIST Laboratories in Gaithersburg, MD and Boulder, CO. For details on this opportunity, see the NIST Postdoctoral Research Opportunities page.

Statistical Methods for Extreme Values, Advisor: Adam Pintar, Location: Gaithersburg, MD

Method Development and Best Practices for Atomic Clock Metrology, Advisor: Amanda Koepke, Location: Boulder, CO

Professional Research Experience Program (PREP)

NIST’s Professional Research and Experience Program (PREP) provides valuable laboratory experience and financial assistance to researchers at various stages of their studies and careers. This official collaboration between participating universities and NIST aims to provide research opportunities to students and graduates.

Researchers from various academic departments apply for PREP appointments. In return, NIST researchers have access to students, recent grads, postdocs, senior researchers, and faculty who bring new ideas and experiences that can strengthen the agency’s research programs. More information can be found here.

Summer Undergraduate Research Fellowship Program

This summer program gives undergraduates the chance to work directly with NIST researchers on real-world projects in statistical modeling, data science, machine learning, and more. More information can be found here.

Statistical Comparisons of Likelihood Ratio Systems for Automatic Speaker Recognition Jack Prothero, jack.prothero [at] nist.gov (jack[dot]prothero[at]nist[dot]gov)

State-of-the-art automatic speaker recognition methods rely on likelihood-based statistical inference to draw conclusions. This category of inference itself includes several approaches, and the choice of approach greatly impacts the performance and interpretability of the speaker recognition system. This opportunity will involve training and testing a variety of frequentist and Bayesian models on a benchmark speaker recognition dataset. The results of these experiments will directly inform professional standards development for forensic speaker recognition. An ideal candidate for this opportunity will be familiar with fundamentals of probability and statistics and preferably have experience with statistical programming tools in Python or R.

Method development and best practices for atomic clock metrology Amanda Koepke, amanda.koepke [at] nist.gov (amanda[dot]koepke[at]nist[dot]gov)

NIST researchers recently demonstrated that optical atomic clocks can make frequency ratio measurements with 18-digit accuracies, a significant advance towards the future redefinition the second, with implications for GPS accuracy and dark matter detection. However, these optical clocks are more prone to down time than the microwave clocks used in the past, creating “gappy” data which often strain, or outright violate, the assumptions underlying the statistical models currently used. This project centers around investigating and advancing our new and improved method for the analysis of clock data using a multitaper spectral analysis approach.

High School Internship Program

Students interested in science can spend their summers in our labs at the Boulder, CO, or the Gaithersburg, MD, campuses through NIST’s Summer High School Intern Program (SHIP). Students learn from top scientists at NIST and work on your own research project. SHIP is an eight-week, unpaid educational internship. Applicants MUST live near NIST Boulder or NIST Gaithersburg Campus. Students need to provide their own housing and transportation. More information can be found here.

Please see the ITL page for more opportunities and information.

Created June 24, 2025

Was this page helpful?