In the Science, Engineering and Technology Group of KU Leuven, Faculty of Engineering Science, Department of Computer Science, there is a full-time tenure-track academic vacancy in the area in natural language processing and multimedia interaction on Campus Arenberg. We seek applications from internationally oriented candidates with an outstanding research track record and excellent didactic skills. The successful candidate will perform research in the Human-Computer Interaction research unit and teach and engage in an appropriate amount of service in the Department of Computer Science.
Learning meaningful and useful representations of unstructured language and multimedia data is a research topic of large current interest. The representations, which are often continuous in nature and realized with deep learning techniques, make it easier to extract useful information from language and multimedia data. They have the potential to be integrated in innovative models for interaction with machines, for instance, in human-machine communication, or in automated search, classification, mining and recommendation of web data. Possible application areas to valorize the research regard automated understanding of language, natural language and multimodal interaction with machines, chatbots, cross-lingual and cross-modal machine translation, information retrieval and question answering, content-based recommendation, online retail, and the mining of text and multimedia data in web, social media and professional settings. Research in representation learning also provides possibilities to outreach to the domain of computer graphics where this approach becomes increasingly important.
The successful candidate will acquire competitive funding and actively participate in the development of future research projects resulting in a coherent research programme that extends an existing research line on the above themes in the Human-Computer Interaction unit of the Department of Computer Science. Research collaboration especially with the Processing Speech and Images unit of the Department of Electrical Engineering (ESAT) is encouraged. The recruitment and supervision of doctoral students are equally part of the assignment.
The candidate is expected to provide state-of-the-art teaching on the above research topics (for instance, in the Master of Engineering: Computer Science, the Advanced Master of Artificial Intelligence and the Master of Applied Informatics at KU Leuven). The candidate should also be willing to take up some educational tasks in bachelor programmes.
You develop your courses in accordance with KU Leuven’s vision on activating and researched-based education and make use of the possibilities for the educationalist professionalization offered by the faculty and the university. Your teaching task will be determined in consultation with the department and will be based on your specific profile.
You are prepared to provide scientific, societal and internal services.
You hold a PhD in Computer Science (or a relevant equivalent degree) with focus on natural language and multimedia processing. You have excellent knowledge of the fundamental principles, algorithms and methods of machine learning and in particular of learning representations (including deep learning) of unstructured language and multimedia data. Good knowledge of inference and optimization techniques will be considered as an asset. You possess outstanding didactic skills and have an excellent track record in research evidenced by publications in top-tier conferences and journals. You possess excellent organizational skills and a strong sense of team spirit. You have an excellent command of the English language.
The official administrative language used at KU Leuven is Dutch. If you do not speak Dutch (or do not speak it well) at the start of your employment, KU Leuven will provide language training to enable you to take part in meetings. Courses will be taught in English or Dutch. Before teaching courses in Dutch, you will be given the opportunity to learn Dutch to the required standard.
We are offering full-time employment in an intellectually challenging environment. KU Leuven is a research-intensive, internationally oriented university that carries out both fundamental and applied scientific research. It is highly inter- and multidisciplinarily focused and strives for international excellence. In this regard, it actively works together with research partners in Belgium and abroad. It provides its students with an academic education that is based on high-quality scientific research.
You will work in Leuven, a historic, dynamic and lively city located in the heart of Belgium, within 20 minutes from Brussels, the capital of the European Union, and less than two hours from Paris, London and Amsterdam.
The tenure track of a junior professor lasts 5 years. After this period and subject to a positive evaluation of the tenure track, he/she will be permanently appointed as an associate professor.
For more information please contact Prof. dr. ir. Stefan Vandewalle, tel.: +32 16 32 76 54, mail: firstname.lastname@example.org or Prof. dr. ir. Philip Dutré, tel.: +32 16 32 76 67, mail: email@example.com.
For problems with online applying, please contact firstname.lastname@example.org.
Add to your application following documents (more information is available on the KU Leuven job site):
- your biosketch in which you indicate your added value as an academic for research, education and service to society of your past career and of your future activities (maximum 2 pages);
- a file on your five most important publications or realizations;
- an extensive cv including a full publication list;
- your research plan with focus on the development of your research line and research team in relation with the colleague-researchers of the entity of employment (maximum 5 pages);
- your vision on academic education and its organization (maximum 2 pages);
- your contribution to society by outreach and public communication on science and technology, internal representation in boards and councils and service activities directly in relation to your developed expertise (maximum 1 page);
- your vision on leadership (maximum 1 page).