POSTDOCTORAL POSITION IN MULTILINGUAL TEXT MINING

22 June 2018

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Interested?

Excellent candidates will be invited for an interview (possibly via Skype).

You can apply for this job no later than July 31, 2018 via the online application tool
KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR@kuleuven.be.

Apply before 31 July 2018

We offer a two-year postdoctoral position funded by the EU ITEA3 project PAPUD "Profiling and Analysis Platform Using Deep Learning” (https://itea3.org/project/papud.html). The principal investigator is Prof. Sien Moens. The scope of the project is to build a universal model for data analytics using deep learning in order to help today’s businesses to make sense out of data.

The postdoctoral position focuses on multilingual text mining and more specifically on interlingual content representations and methods of transfer learning with applications in multilingual topic modelling, content classification (e.g., opinion and argumentation mining) and question answering. The candidate will perform cutting-edge artificial intelligence research in the context of a European consortium composed of renowned academic and industrial partners. 

The research team
The Language Intelligence & Information Retrieval (LIIR) lab of KU Leuven, Belgium is part of the Human Computer Interaction (HCI) unit in the Department of Computer Science. The members of the lab are especially interested in natural language processing and understanding, multimedia mining, machine learning and information retrieval. They study well-informed theoretical models as well as challenging applications, often empowered by big data sets. They investigate probabilistic graphical and deep learning models, with a special focus on learning with limited supervision. LIIR has a special interest in statistical multimodal representation learning where we explore the complementarity of language and visual data. The developed technologies are, among others, applied in the domains of bioinformatics, business intelligence, e-commerce analytics, electronic message filtering, news search and mining, user generated content mining, and World Wide Web mining and search, and contribute to the field of data science in these areas. Through its collaborations LIIR connects to other disciplines including speech processing, computer vision, data mining, artificial intelligence, cognitive science, and human-computer interaction.

The university
KU Leuven is situated in a historic university town close to Brussels, the capital of Europe. It features an excellent Computer Science department providing a stimulating research environment. All programmes at this university are based on the innovative research of its scientists and professors. KU Leuven ranks among the best 50 universities worldwide!

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Responsibilities

* Research, design, develop and evaluate machine learning methods for multilingual text mining. 
* Carry out some teaching duties, which may include lectures/exercise sessions, the organization of student seminars, and the supervision of bachelor or master theses.

Profile

* You have (or are near completion of) a PhD in Computer Science (or a related field). 
* You have a motivated interest in and knowledge of text mining and machine learning, including probabilistic graphical models and deep learning. 
* You have a solid track record of publications in relevant international peer-reviewed A ranked conferences and journals.
* You have a profound interest in collaborating with the industry on applications of text mining and willing to contribute to a deep learning text analytics platform.
* You have a very good knowledge of English, both spoken and written.
* You are highly motivated, ambitious and result-oriented.
 

Offer

* We offer a two-year postdoctoral position, starting in September 2018 (negotiable).
* We offer a competitive wage and yearly budget to attend conferences.