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  3. PhD Position in Content Adaptation & Personalization in Online Media

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PhD Position in Content Adaptation & Personalization in Online Media

The role of the VU in this project is to bring expertise in the area of user modelling, personalization and linked data knowledge engineering in the context of recommender systems (building on results from past ...

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De Boelelaan, Amsterdam, Noord-Holland
Tijdelijk contract / Tijdelijke opdracht
Uren per week:
40 uur
€ 2222 - € 2840 per maand


The role of the VU in this project is to bring expertise in the area of user modelling, personalization and linked data knowledge engineering in the context of recommender systems (building on results from past projects, e.g. CrowdTruth, NoTube and VistaTV projects). VU will be coordinating the work package on Content Adaptation, Re-Purposing and Scheduling by providing the components for viewer profiling and content recommendation. Moreover, it will also contribute with its expertise in linked data enrichment, and with its expertise in user-centred design practices.

The PhD position in this project will be working in a close collaboration with the VU PostDoc within the same project (vacancy number: 18018), and with the corresponding partners in the ReTV consortium. The PhD will be part of the User-Centric Data Science group ucds.cs.vu.nl/


To fill the PostDoc position for this project, we will be looking for an enthusiastic candidate with a strong motivation and the ability to proactively tackle the project’s research questions and do experimental research. The candidates should have a PhD in either computer science, information science or artificial intelligence, and have an outspoken interest in video, entertainment media and TV domain (in terms of users, applications and content). Experience with data modelling (linked data) and data analysis techniques, in particular data science, is considered as another advantage. The candidate must be proficient in English.


The appointment will be initially for a period of 1 year with the possibility to extend with 2 years.

You may find information about our excellent fringe benefits at http://www.workingatvu.nl.
• Remuneration of 8.3% end-of-year bonus and 8% holiday allowance;
• Participation in a solid pension scheme (ABP);
• A minimum of 29 holidays in case of full-time employment.

The salary will be in accordance with university regulations for academic personnel, and range from a minimum of € 2222,00 gross per month in the first year up to a maximum of € 2840,00 gross per month (salary scale 85.0-3 CAO NU) based on a full-time employment.

Additional information

The project, which will host this PhD position is called ReTV (Enhancing and Re-Purposing TV Content for Trans-Vector Engagement) and is a Research and Innovation action funded within the H2020 research framework. The key areas this project will touch on are: Web Information Systems, TV lntelligence, TV Analytics, Audience Research, Format Research. Audience Analytics, Viewer Profiling, Data Analytics, Information Visualisation, Content Recommendation, Content Scheduling. Following is a short description of the project:

Re-purposing and re-using digital content is of vital importance to broadcasters and other stakeholders in European media value chains. High initial production or acquisition costs need to be recouped, but the abundance of online channels creates a thin viewer market for original content, especially on niche topics. Live and on-demand viewing is now spread across Smart TVs, Web and mobile applications, social media and other emerging platforms (to be referred to as “vectors”). This introduces an important challenge: How should broadcasters decide when, in what form and on which vector(s) to deliver which content? The ReTV project proposes Trans-Vector Platform (TVP) to address this challenge and help media companies gain a competitive advantage through guided content re-purposing and re-publication, on the fly and across vectors. The TVP requires novel methods to extract metadata, predict patterns in the topic-vector-audience matrix, and apply these patterns to enhance and re-purpose content - across vectors and according to predicted audience interests. Thus, ReTV will advance the state of the art in video analysis, video augmentation and annotation, content and audience metrics, prediction and recommendation models, visual analytics. The results of this extensive research will be tested and validated together with a regional public broadcaster (RBB), a national TV archive (NISV) and an OTT TV distributor operating in multiple EU markets (Zattoo). ReTV will offer them a better match between content and viewers across vectors, time and five EU languages (English, German, French, Spanish, Dutch). Impact will be measured via cross-vector deployment and viewer engagement. Automated re-purposing and more accurate targeting in terms of relevance and appropriate representation, tailored to upcoming events and specific vector audiences, will drive growth, lower costs, and increase the competitiveness of broadcasters and other professional stakeholders in European media value chains.

For additional information please contact:
Prof. dr. Lora Aroyo
phone: +31 620329972
e-mail: Lora.Aroyo@vu.nl

Department of Computer Sciences: http://www.cs.vu.nl/

Applicants are requested to write a letter in which they describe their abilities and motivation, accompanied by a curriculum vitae and two or three references (names and e-mail addresses).

Applications should be sent by email before February 15, 2018.
Please mention the vacancy number in the e-mail header.

Any other correspondence in response to this advertisement will not be dealt with.


Vrije Universiteit Amsterdam (VU) is a leading, innovative and growing university that is at the heart of society and actively contributes to new developments in teaching and research. Our university has ten faculties, and provides work for over 4,500 staff and scientific education for more than 23,000 students.

Research at the Faculty of Sciences focuses on the areas of Life & Health, Networked World, Fundamentals of Science, and Energy & Sustainability. The faculty’s teaching activities are directly linked to this excellent research. Cooperation with other faculties on the Vrije Universiteit Amsterdam campus generates attractive, high-quality Bachelor’s and Master’s programmes. At international level, the faculty cooperates closely with leading scientific institutes and other partners.

The VU Department of Computer Science has approximately 170 members, including 35 tenured staff members and 40-50 PhD students. The tenured staff members form the essential basis for the functioning of the department. A tenured staff member is required to make significant contributions to the research and education programmes, and to spend effort on specific tasks at the department level.

The VU Department of Computer Science hosts one of the leading Semantic Web research clusters worldwide. The User-Centric Data Science group (led by Prof. dr. Lora Aroyo, ucds.cs.vu.nl/) is part of this Semantic Web cluster and has a specific focus on human computation, crowdsourcing and collective intelligence, user-centered design practices, semantic technologies for modeling user and context for recommendation systems and personalized access of online multimedia collections, e.g. cultural heritage collections, multimedia archives and interactive TV. Researchers from this group have delivered key contributions to internationally renowned methodologies, frameworks and languages for knowledge engineering, intelligent user interfaces and Semantic Web technologies. They have been active over the years in a wide range of national and European efforts including, recently, ControCurator, SealincMedia, VISTA-TV, NoTube (as coordinator), Open PHACTS, Big Data Europe and EuropeanaConnect. The group has specific expertise in applying its research to applications in the cultural heritage, media and broadcasting domains through close collaborations with institutions such as the Rijksmuseum, BBC, IBM and Europeana. The group specializes in human-computer interaction, human computation, collective intelligence, crowdsourcing, semantic interoperability, semantic annotation, niche sourcing, recommendation systems, and semantic search facilities for distributed data.