General Description

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.

The NIST Statistical Engineering Division seeks a researcher with a broad interest in statistical metrology to work on a variety of problems with NIST scientists, engineers, statisticians and other technical staff. Projects areas are likely to include research in the statistical characterization of nanomaterials to study chemical loading mechanisms in pharmaceutical applications (e.g., vaccine delivery) or assessing environmental contamination (e.g., contaminant adsorption on plastic nanoparticles), forensic science (e.g., analysis of DNA, footwear and tire tread, or other types of evidence), statistical methods for instrument calibration or the development of reference materials, characterization of semiconductor components or processes, or similar projects from a wide range of other physical science application areas. Statistical methods used may include experiment design, linear models, Bayesian modeling via Markov Chain Monte Carlo (MCMC), machine learning, or other techniques required to solve the problems at hand. Problems generally are collaborator-driven by the needs of the NIST technical staff in areas outside of statistics. Each project typically has a duration of several months to several years. Longer-term collaborative projects often have work that occurs in multiple-phases, however, and include publication of intermediate results.

Key responsibilities will include but are not limited to:

• Working with NIST scientists, engineers, statisticians, and other technical staff to understand and precisely define relevant research questions for applications of interest
• Designing experiments using principles of statistical experiment design, as needed, to answer relevant scientific research questions formulated with collaborators
• Preparing data for analysis, as needed, with an emphasis on reproducible data preprocessing pipelines for data sets requiring a significant level of preparation
• Analyzing data using both graphical methods and via statistical modeling fitting and inference using software tools and methods that support research reproducibility
• Developing software tools for analysis of data by other researchers either for specific projects or for specific computational methods (e.g., Shiny apps, R packages, etc.), as needed

§  Presenting results at internal meetings and potentially to external stakeholders

§  Ensuring that research results, protocols, software and documentation, or other work outputs have been shared with relevant NIST staff members or appropriately archived for future NIST use.

Privacy Act Statement

Authority:  15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)

Purpose:  The National Institute for Standards and Technology (NIST) hosts the  Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.  

PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.

Routine Uses:  NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices:  NIST-1: NIST Associates. 

Disclosure:  Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.

Qualifications

§  An MS or PhD in statistics or a related field with a focus on modeling and inference

§  Three to five years of relevant work experience

o   Experience in exploratory data analysis and preprocessing data for analysis

o   Experience using or developing software for statistical modeling and inference

§  Ability to work both independently and in collaborative teams to solve problems

§  Skill in communicating complex statistical concepts to non-statisticians

§  Ability to work 30 to 40 hours/week, in total with academic advisor and potentially one or more other graduate student advisees who apply at the same time via this posting and the associated Academic Affiliate posting

Application Instructions

Interested candidates should submit applications, including a full curriculum vitae, and names and contact information of three professional references. 

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About Johns Hopkins University

Johns Hopkins University remains committed to its founding principle, that education for all students should be grounded in exploration and discovery. Hopkins students are challenged not just to learn but also to advance learning itself. Critical thinking, problem solving, creativity, and entrepreneurship are all encouraged and nourished in this unique educational environment. After more than 130 years, Johns Hopkins remains a world leader in both teaching and research. Faculty members and their research colleagues at the university's Applied Physics Laboratory have each year since 1979 won Johns Hopkins more federal research and development funding than any other university. The university has nine academic divisions and campuses throughout the Baltimore-Washington area. The Krieger School of Arts and Sciences, the Whiting School of Engineering, the School of Education and the Carey Business School are based at the Homewood campus in northern Baltimore. The schools of Medicine, Public Health, and Nursing share a campus in east Baltimore with The Johns Hopkins Hospital. The Peabody Institute, a leading professional school of music, is located on Mount Vernon Place in downtown Bal...timore. The Paul H. Nitze School of Advanced International Studies is located in Washington's Dupont Circle area.

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