Assistant Research Scientist (PREP0004077)

Description

PREP Research Associate (US Citizen)

This position is part of the National Institute of Standards and Technology (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:

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) 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 could include, but are not limited to, leading the following activities:

 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

 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