PhD vacancies at KU Leuven
Machine Understanding for interactive StorytElling
Description: The Department of Computer Science at KU Leuven has an open PhD position in the frame of the European MUSE (Machine Understanding for interactive StorytElling) project. MUSE will introduce a new way of exploring and understanding information by “bringing text to life” through 3D interactive storytelling. Taking as input natural language text like children’s stories or medical patient education materials, MUSE will process the natural language, translate it into formal knowledge that represents the actions, actors, plots and surrounding world, and then render these as virtual 3D worlds in which the user can explore the text through interaction, re-enactment and guided game play.
The PhD student will study advanced natural language processing techniques that enable the translation of natural language text to the necessary knowledge representation based on probabilistic models of translation, latent class paraphrasing models, and automatic methods for acquiring world knowledge from large corpora. He or she will focus on a specific aspect of natural language understanding and will work in a team of senior researchers in the frame of the MUSE project. The student will have contacts with outstanding European groups in the domains of machine reading of text, knowledge representation, cognitive understanding, and virtual storytelling.
The ideal candidate will recently have completed or will soon complete a master in computer science or a similar discipline. He or she has a large interest in natural language processing, statistical and probabilistic modeling, and machine learning. Excellent (honors-level) results in prior studies are required. The candidate is fluent in spoken and written English.
The interested candidate is asked to submit his or her CV and motivation letter to Marie-Francine Moens (Sien.Moens@cs.kuleuven.be) before June 21, 2012.
Latest application date: 2012-20-06.
Start date of the project: 2012-09-01.
Source of funding: EU FP7-296703 Future and Emerging Technologies call.
Duration of the project: 3 years +1 year extra funding available.
Mining of User Generated Content
The Department of Computer Science at KU Leuven has an open PhD position in the frame of cross-media processing of user generated content. User generated content, e.g. available through social networking sites on the Web, offers a wealth of information. The aim of the IWT-SBO project PARIS (Personalized AdveRtisements buIlt fom web Sources), by which the PhD is sponsored, is to study adequate natural language, image and video understanding techniques that mine user generated content. This is challenging as user generated content is often present in language that is not well-formed or in visual material that is not professionally captured. An important application of the PARIS technologies will be personalized advertising, where relevant advertisements are searched and generated that fit the world of living recognized in the user generated content. This requires efficient and scalable methods of “machine understanding” of content that can be applied in an online setting.
The offered PhD position regards the mining and linking of user generated content focusing on the joint processing of text and visual data (collaboration with a computer vision group). The focus is on developing information extraction methods that learn with a minimum of human supervision and that combine uncertain evidences from different sources making use of advanced probabilistic inference methods. An additional focus is to make the methods scalable and efficient for real-time use.
The ideal candidate will recently have completed or will soon complete a master in computer science or a similar discipline. He or she has a large interest in multimedia processing, statistical and probabilistic modeling, and machine learning. Excellent (honors-level) results in prior studies are required. The candidate is fluent in spoken and written English.
The interested candidate is asked to submit his or her CV and motivation letter to Marie-Francine Moens (Sien.Moens@cs.kuleuven.be) before June 21, 2012.
Key words: information retrieval, information extraction, data mining, machine learning, reasoning about uncertainty.
Latest application date: 2012-20-06.
Start date of the project: 2012-09-01.
Source of funding: IWT (SBO-110067).
Duration of the project: 4 years.
