Job description
As part of our Open Science team, you will support us in developing efficient data cleaning processes, comprehensible visualizations, and software specifically for working with audio transcripts of interviews conducted for our research. Your efforts will support two ongoing projects funded by the Open Research Data Program of the ETH Board: (1) openwashdata community and (2) FAIR Data Practices for Qualitative Research in Transdisciplinarity.
Profile
This job is for you, if
- You care about data and code being easily reusable.
- You know how to use standard data science tools (Git, GitHub, R, Python, RStudio IDE, VS Code).
- You know your way around the collection of R Tidyverse packages, and you are a competent practitioner in solving problems as outlined in the book R for Data Science.
- You stay up-to-date on the latest technical developments for Large Language Models (LLMs) and their use in academia.
- You question existing processes and bring in new ideas.
- You are at an early stage in your career and are looking for project experience at an academic institution.
We offer
We are a small and committed team of 15 people with a collegial culture. We value transparency and openness over scientific publications. We like to share our knowledge with others and allow for creativity and new technologies in our work processes. We reflect on our work and constantly improve it. We believe that the world can be improved with open data.
Everyone is welcome here, just as they are. Our collegial and respectful interaction creates a pleasant working atmosphere and room for new ideas. In addition to a central work location in Zurich with plenty of room, you can work occasionally from home. The employment conditions are based on the university guidelines. They include, for example, five weeks’ vacation, a wide range of training and continuing education opportunities.
Working, teaching and research at ETH Zurich
We value diversity
Curious? So are we.
We look forward to receiving your online application with the following documents:
- A link to an online portfolio of previous work that shows the programming code for a data analysis project (if no public portfolio exists, you can submit a script with programming code with the application package)
- An updated CV in your current format
- A 1-page cover letter that describes how you organize yourself. How do you start your work day? How do you end it? Do you use tools to stay organized, if so, which are those?
The application and selection process will follow these dates:
- 2025-03-31: due date for submission of application
- 2025-04-02: notification about passing the first selection round (three selected candidates)
- 2025-04-07 to 2025-04-10: a day reserved for a personal and a technical interview
- 2025-04-11: notification about selection
More information about the interview process:
The interview will be remote. The personal interview will be 45 minutes long and will be attended by Lars Schöbitz. The technical interview will be 45 minutes long and tests your proficiency in the R programming language, focusing on the collection of R Tidyverse packages. You will share your screen while solving a set of programming tasks. Lars Schöbitz will be available to answer questions and provide support. We will introduce you to other team members with whom you can discuss any questions you may have about working in our group.
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Further information about Global Health Engineering can be found on our website. Questions regarding the position should be directed to Lars Schöbitz, email (no applications).
