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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:
Process Modeling using Physically Informed Machine Learning
The work will entail:
§Designing and training physics-informed machine learning (PIML) models for the prediction of physical and chemical properties using data from experiments and computation constrained by physics requirements.
§Implementing algorithms to assess the performance of PIML models.
§Assessing uncertainty in the predictions of PIML models.
§Developing systems for multiscale modeling of atomic layer deposition processes.
§Developing software to implement the goals stated above (most likely in Python).
§Disseminating results through posters/seminars and international meetings and meeting seminars.
§Ensuring that all results, findings, data, software, etc. are correctly archived and transmitted through appropriate channels.
Key responsibilities will include but are not limited to:
Algorithm development, implementation, and analysis
Analyze heterogeneous data sources.
§Presenting results at internal meetings, and occasional meetings with external stakeholders.
§Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization.
Qualifications
§A Ph.D degree in Chemistry, Physics, Mathematics, Computer Science, Data Science, or a related field.
§Significant course work in one or more of chemistry, physics, mathematics, statistics and/or computer science.
§Familiarity with one or more chemical process modeling packages (e.g. Cantera, CHEMKIN).
§Familiarity with one or more AI/ML software packages (e.g. Tensorflow or Pytorch).
§Ability to program in a modern computational language (e.g. Python).
§Strong oral and written communication skills.
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. Please DO NOT include telephone numbers, home address or photos on your resume.
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.
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.