Postdoctoral Position in Exposure to Dissimilar Views in the Media

Amsterdam, Netherlands
€3,475 to €4,757 gross per month
07 Aug 2019
End of advertisement period
31 Aug 2019
Contract Type
Fixed Term
Full Time

Closing date     31 August 2019
Level of education     PhD
Hours     38 hours per week
Salary indication     €3,475 to €4,757 gross per month

The Amsterdam School of Communication Research ASCoR is the research institute in Communication Science at the University of Amsterdam. It is the largest research institute of its kind in Europe and is among the largest worldwide. More than 50 senior researchers are permanently associated with ASCoR, and its English-language PhD program has more than 35 students.

We currently have a Postdoc vacancy as part of the ERC Starting Grant entitled 'Citizens exposed to dissimilar views in the media: investigating backfire effects' directed by Dr Magdalena Wojcieszak. The vacancy will be linked to the Personalized Communication Project and the Digital Communication Methods Lab, part of the RPA project Communication, directed by Prof. Claes de Vreese.

Project description

In the current polarized climate, understanding between those who hold different views is needed more than ever. Exposure to dissimilar content that challenges one’s beliefs is hoped to foster tolerance. However, exposure to difference can also increase polarization and conflict among citizens with different opinions.

We do not know when and why exposure to dissimilar views amplifies or attenuates hostilities. This project addresses this question. We investigate (1) individual, social, and system factors that together drive exposure to dissimilar views in mass media and online, and (2) the effects of exposure to dissimilar views polarization, while (3) accounting for various political issues and intended and incidental exposure.

The key themes included in this project are:

  • Under what conditions does exposure to dissimilar political views occur?
  • What factors – including individual-level characteristics, political discussion, and media and political system – encourage people to see dissimilar content offline and online?
  • Do these factors vary depending on a political issue?
  • Under what conditions does exposure to dissimilar political views backfire?
  • What are the immediate and overtime effects of dissimilar exposure?
  • What are the individual-level, meso-level, and system-level factors that enhance or minimize polarization?
  • For whom, when, and why does dissimilar exposure lead to polarization and for whom it generates understanding toward citizens with different views?

We combine three methods and advance the use of behavioural data:

  • Panel Surveys – we will conduct panel surveys on systematic samples in three countries (the Netherlands, Poland, and the United States);
  • Online behaviour tracking - concurrently, we will track the actual online exposure among the same participants to identify the specific political content that each participant sees on determined political issues;
  • Automated Content Analysis – we will use existing software and/or supervised machine learning to assess the content’s tone, positive or negative toward each issue. When combined with information on individual attitudes, the content data will tell us whether the content is like-minded or dissimilar with regard to each individual’s attitudes.


You should:

  • have research interest in the topic of the project, and knowledge of new technologies, platforms and capabilities;
  • have a background in communication science, political science, and/or computer science;
  • have proven expertise in quantitative research methods;
  • have extensive experience with Computational Social Sciences and/or Data Science, including proven knowledge of Python and R for data collection and analysis;
  • have expertise in designing, executing and analyzing complex research designs that combine self-reports (experiments/surveys) with digital trace data (e.g., tracking data);
  • have knowledge of - and proven experience with - collecting and analyzing online tracking data and online content;
  • have the willingness and commitment to work in a small, multi-disciplinary team;
  • have an excellent written and spoken command of English, as demonstrated by publications in English-language journals;
  • have excellent organizational, communicative, and presentational skills;
  • hold a relevant PhD degree in behavioural or social sciences or in disciplines relevant to the project. Candidates who are due to submit their dissertation manuscript in 2019 are welcome to apply.

The candidates will be part of the Amsterdam School of Communication Research, University of Amsterdam (and of the AmDigital Communication Methods Lab and the Personalized Communications Project), and lead the development of innovative infrastructure, tools and methods that can advance Communication Science research about exposure to information in online settings.

Further information

You may address questions about the application procedure and other general questions to:

ASCoR Secretariat

Questions about the project content you may address to:

Dr Magdalena Wojcieszak


The position concerns, in principle, a two-year period after an initial test period. The final implementation position is pending contractual approval.

Your monthly gross salary will range, depending on your knowledge and experience, between €3,637 and €4,978 (Scale 11) based on a full-time basis.

We offer a pension scheme, a holiday allowance of 8% per year, and flexible employment conditions. Conditions are based on the Collective Labour Agreement of Dutch Universities is applicable.

Job application

The UvA is an equal-opportunity employer. We prioritise diversity and are committed to creating an inclusive environment for everyone. We value a spirit of enquiry and perseverance, provide the space to keep asking questions, and promote a culture of curiosity and creativity.

The deadline for applications is 31 August 2019. To apply for this position, please add at least the following documents in English:

  • motivation letter, including a brief discussion about how you fit with the topic and objectives of the ERC project lab;
  • curriculum vitae, including publication list and overview of academic activities and achievements thus far (e.g., conference visits, courses taken, awards);
  • proof of your PhD degree. If you have not completed your degree at the time of application, please provide a statement from your supervisor confirming the expected date of completion of your degree.
  • an academic writing sample in English (e.g., journal article, PhD dissertation).
  • a list of names that could be consulted by the RPA as a reference for the candidate (no reference letters required).

Please send all your documents in PDF or doc(x) format to the link below. Only complete applications will be considered.

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