• Postdoctoral Fellow (PREP0003547) - #Faculty

    Johns Hopkins University (Gaithersburg, MD)


    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:

    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    • Ensuring that results, protocols, software, and documentation have been archived or otherwise transmitted to the larger organization.

    • 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.

     

    Salary: $84,000-$89,000 a year

    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) (https://www.nist.gov/iaao/academic-affairs-office/nist-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.

    Job Type: Full Time

    The listed salary range represents the minimum and maximum Johns Hopkins University offers for this position, based on a good faith estimate at the time of posting. Actual compensation will vary depending on factors such as location, skills, experience, market conditions, education, and internal equity. Not all candidates will qualify for the highest salary in the range.

     

    Johns Hopkins provides a comprehensive benefits package supporting health, career, and retirement. Learn more: https://hr.jhu.edu/benefits-worklife/.

     

    Equal Opportunity Employer

     

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

    EEO is the Law

    https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf