The section

Inequality and Public Economics

at

KOF

Swiss Economic Institute is looking for a

Student Assistant

(30%)

.

The KOF Swiss Economic Institute at ETH Zurich is the leading institute for applied research in economics in Switzerland. KOF has a strong collaborative environment that promotes exchange between research and administrative staff at different levels and in different functions and is committed to rigorous, applied research on policy-relevant topics with a connection to Switzerland.

You will work on an ongoing research project on intergenerational mobility in Switzerland which addresses questions of social mobility across multiple dimensions. In particular, the project examines income mobility and related outcomes across generations, focusing on differences by gender, career trajectories, and perceptions and beliefs about intergenerational mobility. The project is led by Dr. Isabel Z. Martínez and is based on rich administrative and survey data from Switzerland.

The position offers the opportunity to gain insight into rigorous empirical research and to contribute actively to the day-to-day work of a research team.

Your tasks include:

• Support in general research activities related to intergenerational mobility in Switzerland
• Analysing data primarily using the statistical software Stata
• Conducting cluster analysis in Python or R
• Conducting literature searches and summarising relevant academic research
• Assisting with the design, implementation, and evaluation of internal surveys

The preferred starting date for this position is

March 2026

, with some flexibility for a later starting date.

We are looking for a highly motivated team member who is interested in gaining insight into applied empirical research.

Ideal candidates bring:

• Strong interest in applied microeconomic research, particularly in inequality and intergenerational mobility in Switzerland
• Completed bachelor’s degree (or close to completion) or ongoing master’s degree in economics or another quantitative social science, with substantial coursework or formal training in data science/econometrics
• Basic knowledge of the statistical software package Stata and a strong willingness to further develop methodological skills
• Basic knowledge of Python or R and a demonstrated interest in machine learning methods, particularly with respect to cluster analysis
• Fluency and excellent writing skills in English
• Knowledge of German and/or French is an advantage

You must be enrolled at a Swiss University and willing to work on-site at KOF between 1 to 2 days per week (max. 15h per week during the semester). At KOF, working time is typically handled very flexibly such that you can take time to study for exams or fulfill other obligations for your studies while coordinating with the research staff at KOF when tasks need to be completed. During the semester break it is possible to work up to 41h per week.

In line with

our values

, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our

Equal Opportunities and Diversity website

to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us - we are consistently working towards a

climate-neutral future

.

We look forward to receiving your online application with the following documents:

• Cover letter (short)
• Curriculum vitae
• Transcript of records of studies up to date or graduation records
• An estimation of your ability and skills separately for Stata, Python, and R on a scale from 1 (beginner) to 5 (proficient)
• At least two writing samples (e.g., a semester-, seminar- or Bachelor's thesis)

Please submit your application by

February 20, 2026

. The position will remain open until filled. Applications are accepted exclusively through our online application portal. Applications via email or postal services will not be considered.

).