Atomic Layer Deposition
Overview
Position: PREP Research Associate (CHIPS Funded Project) with the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). This position supports collaboration with academic researchers on a funded project.
Location: Gaithersburg, Maryland | Type: Full-time | Salary: $84,000–$89,000 per year
Research Title Process Modeling using Physically Informed Machine Learning
Responsibilities
Designing and training physics-informed machine learning (PIML) models for predicting 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 meetings/seminars.
Ensuring that all results, findings, data, software, etc., are correctly archived and transmitted through appropriate channels.
Presenting results at internal meetings and occasional meetings with external stakeholders.
Ensuring that results, protocols, software, and documentation are archived or transmitted to the larger organization.
Qualifications
A Ph.D. degree in Chemistry, Physics, Mathematics, Computer Science, Data Science, or a related field.
Significant coursework 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 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
Limit CV to 3 pages and include a valid email address for contact information. Do not include telephone numbers, home addresses, or photos on the 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 of Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP), 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.
Routine Uses:
NIST will use the information collected to review applications to determine eligibility and to meet programmatic requirements. Disclosure is subject to the Routine Uses identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure:
Furnishing this information is voluntary. By applying to a CHIPS-funded PREP opportunity, you acknowledge that participation requires signing a Non-Disclosure Agreement (NDA) prior to beginning work.
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Location: Gaithersburg, Maryland | Type: Full-time | Salary: $84,000–$89,000 per year
Research Title Process Modeling using Physically Informed Machine Learning
Responsibilities
Designing and training physics-informed machine learning (PIML) models for predicting 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 meetings/seminars.
Ensuring that all results, findings, data, software, etc., are correctly archived and transmitted through appropriate channels.
Presenting results at internal meetings and occasional meetings with external stakeholders.
Ensuring that results, protocols, software, and documentation are archived or transmitted to the larger organization.
Qualifications
A Ph.D. degree in Chemistry, Physics, Mathematics, Computer Science, Data Science, or a related field.
Significant coursework 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 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
Limit CV to 3 pages and include a valid email address for contact information. Do not include telephone numbers, home addresses, or photos on the 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 of Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP), 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.
Routine Uses:
NIST will use the information collected to review applications to determine eligibility and to meet programmatic requirements. Disclosure is subject to the Routine Uses identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure:
Furnishing this information is voluntary. By applying to a CHIPS-funded PREP opportunity, you acknowledge that participation requires signing a Non-Disclosure Agreement (NDA) prior to beginning work.
#J-18808-Ljbffr