Research Assistant in Environmental Economics
Immigration Policy Lab
Zurich, Switzerland
Research Assistant in Environmental Economics
10%-30%, Zurich, fixed-term
As part of an SNSF-funded Ambizione project, Dr Sarah Meier studies the economic dimensions of forest loss and environmental change, with a focus on biodiversity, human well-being, and policy design. The project examines how interconnected natural and economic systems shape outcomes related to land use, conservation, and climate-related risks.
We are seeking a Research Assistant for 6 months, with the option to extension. The position is available immediately or by agreement. Applications will be reviewed on a rolling basis. The role supports ongoing research activities within the project, including engagement with academic literature, empirical analysis, and data work.
This position requires the ability to engage rigorously with academic research. Responsibilities include critically assessing published work, understanding empirical and theoretical approaches, and contributing to the synthesis of research insights. The role is suited to candidates with a strong interest in environmental economics, excellent analytical skills, and the capacity for independent, critical thinking.
Project background
Environmental change is increasingly shaped by interconnected systems linking land use, biodiversity, climate, and human well-being. Forest loss, driven by both human activity and climate-related hazards, has wide-ranging economic, ecological, and social consequences. While a substantial body of research examines these processes, insights remain fragmented across disciplines and often fail to capture broader system-wide interactions.
This project investigates the economic dimensions of forest loss and its implications for biodiversity, human health, and policy design. It aims to develop a structured understanding of these interconnected processes by integrating insights from existing research with empirical analysis. Particular emphasis is placed on identifying gaps in the literature, analysing underlying economic mechanisms, and generating policy-relevant evidence using causal inference methods and spatial data.
Job description
- Engage with and synthesise academic literature in environmental and climate economics
- Critically assess empirical and theoretical research
- Support data collection, cleaning, and management
- Contribute to empirical analysis, with a focus on causal inference methods
- Assist with geospatial data collection, cleaning and visualisation
Profile
- Currently and for the duration of the RA period enrolled in a Master’s programme at a swiss university or ETH
- Bachelor’s degree in economics
- Strong interest in environmental, resource, or climate economics
- Good understanding of empirical methods and causal inference
- Experience with data analysis; knowledge of Python is an advantage
- Familiarity with geospatial data or tools such as ArcGIS is appreciated
- Strong analytical skills and the ability to work independently
- Excellent written and spoken English
Workplace
Workplace
We offer
- Opportunity to work closely with Dr Sarah Meier within an SNSF-funded Ambizione project
- Exposure to ongoing research in environmental and climate economics
- Structured guidance and feedback throughout the project
- Insight into academic research processes and the development of research outputs
- Flexible working arrangements within a supportive research environment
We value diversity and sustainability
Curious? So are we.
We look forward to receiving your online application with the following documents:
- CV
- Short motivation letter
- Transcript of records (Bachelor’s degree)
Further information about the Department of Management, Technology, and Economics can be found on our Website. Questions regarding the position should be directed to Sarah Meier, sarah.meier@mtec.ethz.ch (no applications).
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.