SULI - ESIA - Sayre, Jack - 2.27.2026

Argonne National Laboratory•Lemont, IL

21h

About The Position

The transition of the R&D GREET model from current Excel and .NET platforms to PyGREET (a Python-based framework) introduces a matrix-based approach for Life Cycle Analysis (LCA) calculations. Unlike traditional nested loops utilized by GREET.NET, PyGREET uses a technology matrix, effectively a directed graph adjacency matrix, to represent supply chain process connections. Using the matrix-based approach, PyGREET can efficiently formulate and solve the linear system of the product systems. This approach also provides a unique opportunity to develop a “Material Flow Tracking" system that can traverse the directed graph to track the flow of a material through each stage of a product system, and pinpoint the processes that dominate environmental impacts (hotspots). Core Tasks for the Student: Matrix architecture exploration: Examine the existing matrix-based implementation in PyGREET to understand current interfaces and data flows. Identify stable integration points for accessing the technology matrix without modifying or disrupting the core calculation engine. Backend module development: Design and implement a dedicated postprocessing module for material flow tracking and impact dominance analysis. To preserve the monolithic architecture and avoid performance degradation, the module must: Use an appropriate design pattern to remain decoupled from the main solver. Implement lazy evaluation so analyses are executed only on demand, when a user explicitly requests a detailed supply-chain deep dive. Data schema and in-memory storage: Design a results schema capable of organizing complex flow hierarchies (e.g., tracing one kilogram of steel back to iron ore extraction and upstream energy inputs). The schema should support temporary in-memory storage and be extensible for future integration with a frontend dashboard. Functional testing & validation: Develop a comprehensive suite of functional tests to prevent regressions. Validate the material tracking and dominance analysis logic using real-world test cases provided by Argonne analysts, ensuring the methodology correctly identifies the primary drivers of resource depletion. Technical documentation: Produce thorough technical documentation describing the module’s mathematical formulation, post-processed data structures, and integration points within the broader PyGREET software stack.

Requirements

The entirety of the appointment must be conducted within the United States.
Currently enrolled in undergraduate or graduate studies at an accredited institution.
Graduated from an accredited institution within the past 3 months; or
Actively enrolled in a graduate program at an accredited institution.
Must be 18 years or older at the time the appointment begins.
Must possess a cumulative GPA of 3.0 on a 4.0 scale.
Must be a U.S. citizen or Legal Permanent Resident at the time of application.
If accepting an offer, must pass a screening drug test

Responsibilities

Examine the existing matrix-based implementation in PyGREET to understand current interfaces and data flows.
Identify stable integration points for accessing the technology matrix without modifying or disrupting the core calculation engine.
Design and implement a dedicated postprocessing module for material flow tracking and impact dominance analysis.
Use an appropriate design pattern to remain decoupled from the main solver.
Implement lazy evaluation so analyses are executed only on demand, when a user explicitly requests a detailed supply-chain deep dive.
Design a results schema capable of organizing complex flow hierarchies (e.g., tracing one kilogram of steel back to iron ore extraction and upstream energy inputs).
The schema should support temporary in-memory storage and be extensible for future integration with a frontend dashboard.
Develop a comprehensive suite of functional tests to prevent regressions.
Validate the material tracking and dominance analysis logic using real-world test cases provided by Argonne analysts, ensuring the methodology correctly identifies the primary drivers of resource depletion.
Produce thorough technical documentation describing the module’s mathematical formulation, post-processed data structures, and integration points within the broader PyGREET software stack.