PhD Fellowship in the Field of Automation in Journalism 2020, Aarhus University, Denmark

The Graduate School at Arts, Faculty of Arts, Aarhus University, in collaboration with the Danish School of Media and Journalism, invites applications for a fully-funded PhD fellowship in Automation in Journalism provided the necessary funding is available. This PhD fellowship is available as of 1 September 2020 for a period of up to three years (5+3). The candidate who is awarded the fellowship must commence his/her PhD degree programme on 1 September 2020. 

The PhD fellowship will be financed by the 2 parties.

The PhD fellowship is advertised within the field of Automation in Journalism.

Big data and automation are increasingly occupying the world of journalism and media. The journalists of the future will have unlimited amounts of data available and at the same time must face competition from automated content curation and moderation, both from established media and not least digital intermediaries such as social media and search engines.

Such automation potentially challenges journalism's core ideal such as "watchdog", ideas about journalistic 'gut feeling', sensitivity to a particular market, and users' particular socio-cultural needs and preferences. Likewise, it becomes relevant to look at whether and how automation and algorithms challenge social good (publicist) ideals that at the same time must be economically viable.

However, the field of 'automation in journalism' is under-researched, not least in Denmark. We are looking for a candidate who is interested in exploring the use or potential of automation in journalism. It is a benefit if the applicant has experience from big data analysis projects.

The candidate will be part of AU Datalab at the University of Aarhus and is expected to enter into academic collaborations at both the University of Aarhus and the Danish School of Media and Journalism and in the theoretical, analytical and methodological cooperation that is being established between the two institutions.

For more information click "LINK TO ORIGINAL" below.