The Sustainability Evaluation and Applied Data Science Lab (SEADS) at University of South Dakota specializes in the integration of Systems Design and Applied Data Science for environmental and socioeconomic evaluation in South Dakota and beyond, with focus on water/air/urban sustainability, climate resilient agriculture, and the ethics of Artificial Intelligence in rural communities.
A (MS/PhD) position is available to join the SEADS lab, with an anticipated start of Fall/27 (August 2027). An earlier start in Spring/27 (January 2027) may be considered for candidates already in the US. The research direction for this position is on the integration of Life Cycle Assessment (LCA) and surrogate Machine Learning (ML) twins to study the energy/water footprints involved in data centers lifecycles in the Northern Great Plains.
Responsibilities:
- Compile, audit, and harmonize public life cycle inventory (LCI) and energy/water datasets relevant to data centers (e.g., USLCI, EPA eGRID, EIA, USGS water use, etc.) into documented, AI-ready formats.
- Build and run LCA models for representative data center scenarios in South Dakota (e.g., grid mix, cooling technology, siting, and weather conditions). Use these outputs to prototype and train preliminary LCA-ML surrogate models.
- Complete a publishable thesis, peer-reviewed manuscripts, conference presentations, and maintain lab code and data documentation. Contribute to stakeholder engagement (e.g., community workshops). Provide teaching assistance and other departmental service activities as needed.
Funding:
This position offers a competitive base salary, tuition coverage, and support for conference travel and professional development. The graduate student will be funded initially for two years (M.Sc., 2027-2029), with a possibility to extend funding for two more years (Ph.D.), pending academic/scholastic performance and availability of funds.
Minimum Qualifications:
- A previous degree in Sustainability/Environmental Science, Engineering, Data/Computer Science, Economics, or other quantitative fields with strong interests in Water/Energy Sustainability.
- Hands-on practice/familiarity with LCA software (SimaPro, OpenLCA), data querying, formatting, and metadata extraction from eco-environmental databases (USLCI, ecoinvent, GaBI, etc.) and public data (EPA, USGS, etc.)
- Quantitative aptitude and coding proficiency analyzing tabular and spatial data (Python, R, ArcGIS/QGIS) - verifiable through coursework, projects, or professional experience.
- Exposure and/or strong interest in machine learning, dynamic systems, and other modeling approaches.
Before applying, please contact Dr. Guillermo Marcillo at guillermo.marcillo@usd.edu with the subject line SEADS_GA_LCA_DC and attach the following materials into one single PDF:
- A recent Curriculum Vitae (CV),
- Unofficial transcripts showing GPA and courses taken
- A Statement (1 page) outlining background, relevant experience, and fit for this specific position.
- Names and contact of three academic references