Project overview: Build a Python workflow that automatically converts EPA ECHO biosolids annual report data (~40 CSVs per year) into a cleaned, standardized GREET-ready database for counterfactual analysis. The workflow should be rerunnable each year as EPA updates the reports and, if feasible, incorporate data from the 9 non-EPA-reporting states. This will allow the use of detailed, facility-level compliance data (biosolids volumes, N content, sludge treatment methods) that has previously only been used in LCA as nationally-averaged statistics or partial use from manual addition. Role of the Student: Automated ingest → cleaning/standardization (e.g., IDs, units) → basic QA/QC checks → export in the required GREET format; assess and integrate compatible state datasets. Deliverables: Python ETL script/pipeline that runs end-to-end for a selected year Brief QA/QC summary and annual update instructions If time: The above EPA reports will miss smaller treatment plants. Thus, if time, the student can integrate other databases using automated workflows to develop a more comprehensive dataset. Other datasets include: Seiple and Ha datasets on sludge production at each facility EPA Clean Water Needs Survey National Biosolids Data Project WEF digester database DOE CHP database ANL RNG database Education and Experience Requirements The entirety of the appointment must be conducted within the United States. Applicants must be: ‒ 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
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Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees