General Description

Salary: $75,000-$82,000 a year

PREP Research Associate
CHIPS Funded Project.

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 and thus requires that such institutions be the recipients 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.

Research Title:

Coupling Computation and Machine Learning to evaluate PFAS Chemicals

The work will entail: 

The position is for a postdoctoral associate level researcher interested and experienced in applied data science to work jointly with chemists, mathematicians, and computer scientists at NIST to participate in the characterization and modeling of properties and spectra of PFAS chemicals with the goals of improving detection of PFAS compounds, replacing PFAS in plasma etching processes, or identifying solid adsorbent additives to remove PFAS. To accomplish these goals, the candidate will participate in the development of AI/ML algorithms for the prediction of chemical properties, infrared and mass spectra, and ionization cross sections, incorporating uncertainty quantification into AI/ML models and providing useful information in aid of UQ in AI/ML models to discern patterns in physical properties. The position will be highly interdisciplinary, requiring regular communication between chemists, computer scientists and mathematicians working on modelling these compounds using experimental as well as data from chemistry/physics calculations/simulations.

Key responsibilities will include but are not limited to:

-         Developing novel machine learning algorithms for the prediction of physical and chemical properties, infrared and mass spectra, and ionization cross sections using data derived from experiment and computation.

-         Implementing algorithms to study the performance of AI/ML classification models.

-         Assessing uncertainty in prediction and classification of experimental data as well as data sets derived from quantum chemistry and physics calculations and simulations.

-         Computationally testing mathematical and machine learning models with respect to accuracy and uncertainty quantification.

-         Developing software to implement the goals stated above (most likely in Python).

-         Disseminating results through posters/seminars at international meetings and university seminars.

-         Ensuring that all results, findings, data, software, etc. are correctly archived and transmitted through appropriate channels.

-         Attending regular meetings to present updates on research and to discuss progress with collaborators.

Qualifications

-         Completed a PhD (or close to completion) in data science or related field.

-         Knowledge of or a desire to acquire knowledge about chemistry.

-         Minimum of 1 year of experience conducting data science research.

-         Significant course work in one or more of chemistry, physics, mathematics, statistics and/or computer science.

-         Familiarity with one or more AI/ML software packages. Familiarity with relevant, domain-specific software packages is preferred but not required.

-         Ability to program in a modern computational language (e.g. Python).

Application Instructions

Please upload the following with your application:

-         CV/Resume

*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.

-         Self portraits

-         Phone number

-         Home address/Country

-         Citizenship status

-         Languages spoken

-         Sex/Gender

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 the 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. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.

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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