Author: Yin-Yin Tan

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. National Institute of Standards (NIST) Professional Research Experience (PREP) program invites applicants in support of applied AI for economic systems science. 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 position is in the Applied Economics Office (AEO), a part of the Engineering Laboratory (EL) at NIST, which provides economic products and services through research and consulting to industry and government agencies in support of productivity enhancement, economic growth, and international competitiveness, with a focus on improving the life-cycle quality and economy of constructed facilities and manufacturing processes that support social and economic functions. AEO is integrated within EL’s major research thrusts. AEO delivers high quality research and tool development that informs and assists stakeholders in their decision-making processes. The position will collaborate directly with the software development team in EL’s ELDST (Engineering Laboratory Data, Security, & Technology) that oversees AEO’s software development projects. Research Title is Performance and efficacy of machine learning and artificial intelligence implementation in economics and life cycle system science decision support

The work will entail:

We are looking for a computer scientist (US citizen preferred) to join our team in researching the performance and efficacy of machine learning and artificial intelligence (large language models – LLMs) across a variety of both research-oriented and public-facing software applications using standardized science-based metrics. The initial focus is on developing LLM-based outputs, and comparing their performance relative to manually developed outputs, including drafting annotated bibliographies and literature reviews, writing code, web applications that incorporate LLMs to enhance capabilities, and LLM-based web applications.

The ideal candidate will have a strong background in integrating LLM APIs, React, and front-end programming, and will be responsible for transforming models into usable APIs or integrated tools for production. They will also be responsible for monitoring, troubleshooting and enhancing model efficiency and scalability. The candidate should also be well versed in handling data preprocessing, and analysis for model training. The candidate should be aware of various prompt engineering techniques,
implementing intelligent prompt caching (e.g., Redis), understanding of vector stores (e.g., Pinecone), and efficient token management. The candidate should have knowledge of implementing AI security protocols, including guardrails and techniques to prevent prompt injection. The candidate should also have a working knowledge of RAG (Retrieval Augmented Generation). Additional research tasks may be assigned based on candidate’s skillset and priorities. Research Title is Performance and efficacy of machine learning and artificial intelligence implementation in economics and life cycle system science decision support.

Key responsibilities will include but are not limited to:

• Develop user interfaces for web application
• Assist with special software development projects as assigned
• Write and implement efficient code
• Document code and publish on GitHub
• Work closely with other developers
• Statistically compare performance across code and tool designs
• Draft manuscripts documenting the methodology and results

Qualifications:

• US Citizen Preferred
• Master’s degree in Computer Science or related field
• At least 2 years of professional experience
• At least 1 year as development team lead for at least one web application using the software stacks listed below
• Experience with state management in React (RxJS)
• Experience working on cloud technologies (AWS, Azure)
• Working knowledge of RAG (Retrieval Augmented Generation)
• Proficient with integrating one or more LLMs into applications (e.g., OpenAI, Gemini, Llama)
• Proficient with HTML, CSS, Typescript, React, and Python
• Proficient using any UI Component libraries (e.g., Ant Design, Material UI, etc.)
• Proficient with Node.js
• Working knowledge of building quick prototypes using Streamlit (or similar) and LLMs
• Proficient with JSON
• Proficient with Vite, Nginx, GitHub, Docker, and Portainer
• GPU programming or data visualization experience a plus
• Evidence of strong oral and written communication skills, including authorship on at least 2 technical publications)
• Strong logical thinking and problem solving
• Excellent attention to detail

Please upload the following (preferably in a single PDF) with your application:

• CV/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 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.

• Announcement and Application

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 position is in the Applied Economics Office (AEO), a part of the Engineering Laboratory (EL) at NIST, which provides economic products and services through research and consulting to industry and government agencies in support of productivity enhancement, economic growth, and international competitiveness, with a focus on improving the life-cycle quality and economy of constructed facilities and manufacturing processes that support social and economic functions. AEO is integrated within EL’s major research thrusts. AEO delivers high quality research and tool development that informs and assists stakeholders in their decision-making processes. Research Title is Life Cycle System Science of Materials and Engineered Systems.

The work will entail:

We are looking for a life cycle assessment (LCA) expert (US Citizen Preferred) to join our team in evaluating materials and engineered systems using life cycle system science. The position will collaborate with NIST researchers and NIST’s external collaborators in a variety of topics relevant to their work including economists, engineers, and scientists – connecting LCA to fundamental research, life-cycle analysis, and decision support tools related to activities across a range of research topic areas: building and infrastructure, energy, circular economy, resilience, and decision science. Initial activities will include developing and updating of LCA models for a variety of construction materials and building systems, semiconductors, microelectronics, and emerging technology recovery pathways, and engineered direct air capture technologies that will be published and maintained in repositories on the Federal LCA Commons.

Key responsibilities will include but are not limited to:

• Review, assessment, and improvements to NIST’s existing LCA data models and decision support tools
• Identify, quantify, and prioritize data gaps in product categories of interest to NIST
• Maintain and expand the Construction Materials and Building Systems repositories on the Federal LCA Commons
• Automate LCA model development workflow for transparency, repeatability, and efficiency
• Review, validation, and analysis of dynamic operational electricity LCA data
• Identify research and data gaps in current LCA-related activities at NIST
• Write research slide decks, reports, and/or journal articles
• Draft NIST research plan for increasing standardization and harmonization in LCA modeling
• Participate in ACLCA committees and sub-committees and LCA-relevant NIST consortia as appropriate

Qualifications:

• US Citizen Preferred
• PhD in Engineering, Environmental Science, or related field
• At least 10 years of experience in life cycle assessment research
• Experience with life cycle assessment of at least five of the following topics: chemicals, plastics, photovoltaics, batteries, carbon dioxide removal, semiconductors, microelectronics, concrete, other building materials, or whole buildings
• Extensive experience with OpenLCA and its developer tools, and public life cycle inventory (LCI) databases, including the Federal LCA Commons repositories and GREET suite of tools
• Experience developing and updating large LCI datasets
• Experience in solving complex LCA-related problems (i.e., long supply chains and production processes, and evaluation of multiple impact indicators and methods
• Excellent writing and communication skills
• Self-driven and capable of working independently with minimal supervision

Please upload the following (preferably in a single PDF) with your application:

• CV/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 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.

• Announcement and Application

This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. National Institute of Standards (NIST) Professional Research Experience (PREP) program invites applicants in support of Materials Life Cycle Systems Science. 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 position is in the Applied Economics Office (AEO), a part of the Engineering Laboratory (EL) at NIST, which provides economic products and services through research and consulting to industry and government agencies in support of productivity enhancement, economic growth, and international competitiveness, with a focus on improving the life-cycle quality and economy of constructed facilities and manufacturing processes that support social and economic functions. AEO is integrated within EL’s major research thrusts. AEO delivers high quality research and tool development that informs and assists stakeholders in their decision-making processes. Research Title is Life Cycle System Science of Materials and Engineered Systems.

The work will entail:

We are looking for a life cycle assessment (LCA) researcher (US Citizen Preferred) to join our team in evaluating materials and engineered systems using life cycle system science. The position will collaborate with NIST researchers and NIST’s external collaborators in a variety of topics relevant to their work including economists, engineers, and scientists – connecting LCA to fundamental research, life-cycle analysis, and decision support tools related to activities across a range of research topic areas: building and infrastructure, energy, circular economy, resilience, and decision science. Initial activities will include developing and updating of LCA models for a variety of construction materials and building systems and emerging technologies and material recovery pathways that will be published and maintained in repositories on the Federal LCA Commons. Specifically, this will include developing and publishing open-source models based on public data for large format battery manufacturing and material recovery pathways and complete a life cycle inventory (LCI) data gap assessment. The position will also be responsible for collaborating with a computer scientist in developing a large language model (LLM) based web application to digitize PDF-based environmental product declaration (EPD) claims using the OpenEPD schema. Additionally, the position will complete statistical analysis of the battery LCA modeling literature as well as assist in validating an LLM literature review support tool. The position will also be responsible for geospatial analysis as needed.

Key responsibilities will include but are not limited to:

• Review, assessment, and improvements to NIST’s existing LCA data models and decision support tools
• Identify, quantify, and prioritize data gaps for large format batteries and other product categories of interest to NIST
• Develop and maintain a repository on the Federal LCA Commons for large format batteries
• Identify research and data gaps in current LCA-related activities at NIST
• Validate LLM-based tools
• Write research slide decks, reports, and/or journal articles
• Participate in ACLCA committees and sub-committees and LCA-relevant NIST consortia as appropriate

Qualifications:

• US Citizen Preferred
• Master’s in Engineering, Environmental Science, or related field
• Experience in ISO compliant LCA modeling and related research
• Experience using OpenLCA
• Experience using public life cycle inventory (LCI) databases, including the Federal LCA Commons repositories and GREET suite of tools
• Experience using technical document reference software (e.g., Zotero, EndNote)
• Knowledge of construction materials and building sciences and systems
• Extensive knowledge of EPDs and OpenEPD JSON schema
• Knowledge of large language model (LLM) applications for document parsing, information formatting, and text summary
• Experience in life cycle assessment of at least 5 of the following: large format batteries, concrete, cement, asphalt, gypsum, other building materials and systems, material recovery pathways, and whole buildings
• Proficient in spatial analysis using GIS-based software (e.g., ArcGIS, QGIS)
• Experience in solving complex LCA-related problems (i.e., long supply chains and production processes, and evaluation of multiple impact indicators and methods)
• Experience writing literature reviews and conducting statistical analysis
• Excellent writing and communication skills, including at least 2 technical publications and at least 2 conference presentations
• Self-driven and capable of working independently with minimal supervision

Please upload the following (preferably in a single PDF) with your application:

• CV/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 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.

• Announcement and Application