Vacancies

The Centre for Media and Journalism Studies (CMJS) is looking for a PhD student in “Investigative journalism and interpretive “deep” reporting” within the HAICu research project.

This specific PhD position explores the development of investigative journalism and interpretive “deep” reporting in Dutch news media. It will study recurring critiques of journalism being too much focused on single news events while missing the broader story these are situated within. The focus of the project will be on the development of investigative and interpretive reporting on migration and discrimination that aims to make sense of news events by situating them in longitudinal developments and debates. It will analyse newspaper, television, radio and online reporting on sensitive political issues and debates on that develop over time using multimodal discourse analysis. It will analyse the interrelatedness of these various modalities and study reporting practices through interviews with journalists.

The project will be supervised by prof. Marcel Broersma and prof. Yael de Haan at the University of Groningen. This is an interdisciplinary project at the intersection of Journalism Studies and Digital Humanities.

Within the dynamic HAICu team, the PhD researcher will participate in Work Package 1, titled “Multimodal AI Research for Multimodal Heritage and Deep journalism”. In this WP, we will collaborate with Journalism Studies, AI and machine learning experts from the University of Utrecht, the University of Amsterdam, Hogeschool Utrecht as well as a range of cultural heritage partners, such as the Dutch National Library and the Netherlands Institute for Sound and Vision.

Apply here!

The Computational Linguistics group (GroNLP) of the Center for Language and Cognition Groningen (CLCG) is looking for a PhD student in “Language technology for cultural heritage: New discoveries with little data” within the HAICu research project. This specific PhD position is about effectively dealing with missing and sparse labels in humanities datasets such as literature, history, philosophy. Cultural heritage institutions, and especially the National Library of the Netherlands, offer access to a lot of digitized data which can be leveraged through computational approaches. However, it is very common that the data is incomplete. This is a challenge for typical machine learning methods that rely on being fed with representative and complete data, leading to systems that cannot handle distribution shifts or extrapolating beyond their training set.

The project will, in collaboration with the National Library of The Netherlands, be coordinated by Andreas van Cranenburgh, Tommaso Caselli, and Malvina Nissim at the University of Groningen. This is an interdisciplinary project at the intersection of Computational Linguistics/Natural Language Processing (NLP) and the humanities.

Within the dynamic HAICu team, the PhD researcher will participate in Work Package 3 (WP3), titled “Learning from sparse examples”. In this WP, we will collaborate with AI and machine learning experts from the University of Tilburg, the Fontys Hogeschool as well as other partners, in addition to the aforementioned Dutch National Library.

Apply here!