Utrecht University is looking for PhD or postdoctoral students for multimodal processing of cultural digital archives at the Interaction Division of Utrecht University, the Netherlands. The deadline for applications is 13 November.
Job description
Are you passionate about developing cutting-edge AI techniques to enhance interaction and communication across multiple modalities, such as text, pictures, audio, and video? Join the large scale HAICu NWA-ORC project to help unlock the potential of cultural digital archives through multimodal use, providing richer context and a more comprehensive analysis of current complex issues in society. If this fits your expertise and interests, the Interaction Division of Utrecht University is seeking you!
Your job
We are looking for a PhD and a postdoctoral researcher to work within the multi-partner HAICu NWA-ORC project. This vacancy is for the Postdoc position, the PhD position is being advertised simultaneously:
PhD Position on Multimedia Analysis in the HAICu Project. There are two research topics tackled in parallel for this project (see description below). Based on the applications, the topics will be assigned at PhD or Postdoc level. Both researchers will collaborate within the project.
This project is implemented by an ambitious consortium including many universities, knowledge institutions, archives, foundations, cultural institutions and business partners in the Netherlands. It aims to use improved access to digital heritage to tutor the Digital Citizen in the use of big data. It brings together AI researchers and Digital Humanities scholars to seek solutions to the problem of inadequate data-mining tools we have, aiming to derive information from the continuous stream of data about the present and the past. This will help citizens and other regular users, heritage curators and journalists who are interested in tapping heritage collections, as well as civic organizations and authorities interested in improving civic participation.
There are two research topics. You can indicate in your motivation letter whether you prefer one or the other.
Research topic 1 targets visual and multimodal feature learning for news ecosystems, analysing the complex multidimensional feature space of visual information to support data-driven journalism. This includes experiments for accountability, transparency, inclusiveness, and misinformation. The key technology is multimodal deep learning, and its extensions for these additional targets.
Research topic 2 targets audio and multimodal feature learning beyond words, such as intonation, tone, stress and rhythm, in relation to conveying emotion or messages, to support data-driven journalism. We will research audio features (e.g. for speech and music) and their relation to effective message conveying in news collections with audio and video, and innovate multimodal search by integrated feature learning in both visual and audio at the same time.
Research will include testing, validation and evaluation on large scale and interoperable collections, in cooperation with the societal partners in the project, including the Netherlands Institute for Sound and Vision, the National Archive, and the National Library of the Netherlands. The research will take place in collaboration with the HAICu fieldlab ‘Deep Journalism’, which develops functionality for searching for items about a similar topic from different archives and with various modalities to support news journalists.
The Interaction Division is part of the department of Information and Computing Sciences. It develops novel techniques to research technology-mediated communication and interaction between people, and communication and interaction between systems and people (users). The technologies for interaction make use of various modalities, in particular visual, auditory, and haptic modes, as well as combinations of these. Three of the chairs in the division are collaborating in this project. The Multimedia group (Professor Remco Veltkamp), the Music Information Computing group (Professor Anja Volk), and the Social and Affective Computing group (Professor Albert Salah).
Postdoc position:
PhD position: