The Social Sciences Institute of the University of Lausanne, in collaboration with the Swiss Centre of Expertise in the Social Sciences (FORS), is offering a

Research Associate position (80%) in the field of quantitative social science

The Faculty of Social and Political Sciences covers the main branches of social and political sciences, constituting the bases of an interdisciplinary knowledge of the interactions between the collective and individual dimensions. The faculty supports a joint research program with the Swiss Centre of Expertise in the Social Sciences (FORS) to foster synergies between the two institutions.

FORS enhances and supports empirical and methodological work in the social sciences by conducting survey as well as substantive research based on the data they produce, in collaboration with members of the faculty. FORS supports methodological excellence and innovation; it is for instance one of the main partners managing the platform dedicated to data linking in Switzerland. FORS is hosted by the University of Lausanne (UNIL) and works closely with the university-based Life Course and Inequality Research Centre (LINES).

Job information

Expected start date in position : May 1st, 2020

Contract length : 24 months, with a possible extension of 12 months

Activity rate : 70-80%

Workplace : Géopolis building, Mouline

Your responsibilities

The UNIL, in collaboration with FORS, offers a postdoctoral researcher position in quantitative methods with a focus on combining and analyzing multiple data sources (such as survey data, administrative data as well social media data). The successful applicant will contribute to FORS’ research in at least one substantive field of social sciences (sociology, political science, economics, psychology, demography, health, etc.), using advanced data linkage methods to combine different data sources and to analyze and evaluate the potentials and challenges of such procedures. The post-doc should also develop and conduct a small innovative project in this area collaboratively with colleagues from LINES and FORS.

The post-doc position will structurally be part of one of the LINES research groups and will be expected to collaborate with members of the survey teams at FORS. The position will also offer the possibility to develop a personal research agenda (50% of working time).

For more information please visit our websites: and

Your qualifications

Applicants are required to hold an advanced academic degree in the social sciences (Dr., Ph.D). They are expected to have advanced quantitative methods for analysis and data management skills as well as skills in collecting, handling and analyzing social media data and other large-scale data. Moreover, it would be desirable if applicants have survey research experience (ideally in the area of data linkage) as well as a scientific publication record in methods and/or a substantial research field.

A fluent command of English (spoken and written) is essential in our multilingual scientific setting. Familiarity with French and/or German are desirable.

What the position offers you

We offer a nice working place in a multicultural, diverse and dynamic academic environment. Opportunities for professional training, a lot of activities and other benefits to discover.

Contact for further information

In case of any questions regarding the position, please contact Prof. Stephanie Steinmetz (UNIL, or the Head of the FORS survey unit, Prof. Boris Wernli (

Your application

Please submit your application (in English, French or German) not later than 23 February 2020 including

  1. Motivation letter
  2. CV, listing the names of two referees
  3. A piece of academic writing as example (journal article, chapter of PhD dissertation etc.)
  4. A project proposal of a potential research topic which can be conducted during the post-doc time and which fits the thematic focus of the position (max. 4 pages)

Please, send your full application in Word or PDF.

Only applications through the University of Lausanne Website will be taken into account !

We thank you for your understanding.

Job description

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