Student Assistant – Data Analysis for Greenhouse Gas Accounting

About the role

The ETH Office of Sustainability is looking for a motivated student research assistant to help improve greenhouse gas (GHG) emission accounting methodologies at ETH Zurich, from December 2026 until March 2027. The work sits within the ETH Net Zero Programme, where accurate emission accounting underpins decisions on the path to net zero. The ideal start date is December 1, 2026, and applications are evaluated on a rolling basis.

Key responsibilities

• Update existing Python scripts to extract the most up-to-date and accurate spend-based emission factors from the underlying databases.
• Improve, develop and benchmark approaches (in Python) for matching procurement data, mostly text descriptions, with emission factor databases, including classical text matching and machine learning / embedding approaches.
• Implement the final approach in a reproducible way that can be applied annually for GHG emission accounting.
• Include supplier-specific emission data in the GHG accounting and investigate ways to integrate publicly available emission databases efficiently (optional).

Required profile

• Enrolled student at ETH Zurich or another Swiss university.
• Strong programming skills (especially Python) and software development experience.
• Interest and experience in data analysis and handling large datasets.
• Knowledge of machine learning methods, large language models and their practical use.
• Experience with R is a plus; interest in sustainability, life cycle assessment or GHG accounting is a plus.
• Independent, structured and solution-oriented way of working.

Required skills

• Python
• Data analysis and handling of large datasets
• Machine learning and large language models
• R (a plus)

What we offer

• A chance to contribute directly to ETH Zurich's net zero goals and Net Zero Programme.
• Hands-on experience at the intersection of sustainability, data science and environmental assessment.
• Regular 1-on-1 meetings and mentoring, and a collaborative team with diverse backgrounds.

Applications must be submitted online by November 30 with a short motivation letter (max. 1 page), current CV, academic transcripts and a brief portfolio or code sample (e.g. GitHub link). Only applications sent through the online portal are accepted.