ERC ADG for Luc De Raedt on Synthesising Inductive Data Models: Job openings for PhD & Postdoc

Link to official KU Leuven vacancy to apply (ref BAP-2016-441):

The Machine Learning research group is searching for PhD candidates and Postdoctoral researchers in the fields of

  • The automating of data science
  • Probabilistic Programming
  • Statistical relational artificial intelligence
  • Constraints programming
  • Data Mining
  • Inductive databases and rule learning

Relevant Projects

  • The ERC Advanced Grant SYNTH (Synthesising Inductive Data Models) expected to start on September 1, 2016. The ultimate goal of the SYNTH project is to automate the task of the data scientist when developing intelligent systems, which is to extract knowledge from data in the form of models. It wants to develop the foundations of a theory and methodology for automatically synthesising inductive data models using artificial intelligence, data mining, machine learning and probabilistic methods; see
  • FWO projects related to probabilistic programming, relational learning and their applications in robotics; here the goal is to develop fast methods for inference in probabilistic programming and databases; such programming and database languages allow to express uncertainty using artificial intelligence techniques,and the underlying models can also be learned from data.

A more comprehensive overview of the research topics can be found at

DTAI Research group

The lab for Declarative Languages and Artificial Intelligence hosts about 12 professors, 6 post-docs and 40 PhD students. DTAI is internationally renowned for its expertise in integrating different forms of reasoning (inductive, deductive and probabilistic), in logical learning, statistical relational learning, probabilistic programming, learning from structured data (relational databases and graphs), inductive logic programming, inductive databases, action-activity learning, knowledge representation and data mining, and constraint programming.

Next to fundamental research in machine learning and data mining, the DTAI group applies the developed techniques to concrete cases situated in intensive care monitoring, predictive maintenance, smart self-diagnosis, mechatronics, robot manipulation and navigation, bio- and chem-informatics, natural language processing, smart electronics, computer vision, etc. For these applications, DTAI cooperates with other groups from strategically chosen research areas. 

KU Leuven

Situated in Belgium, in the heart of Western Europe, KU Leuven has been a centre of learning for nearly six centuries. Today, it is Belgium's largest university and, founded in 1425, one of the oldest and most renowned universities in Europe (ranked 82nd in the QS World Universities Rankings and 35th in Times Higher Education). As a leading European research university and co-founder of the League of European Research Universities (LERU), KU Leuven offers a wide variety of international master’s programmes, all supported by high-quality, innovative, interdisciplinary research. It counts about 11,500 staff and 57,000 students, including 7,500 international students representing 146 nationalities.

Since its founding, KU Leuven has been based in the city that shares its name. Leuven is a pleasant, safe and bustling student town, where centuries-rich history meets cutting-edge science.


The ideal candidate is a computer scientist with interest and expertise in artificial intelligence, databases, data mining, machine learning, and/or probabilistic graphical models. He/She is interested in theory, a skilled programmer, and excited about applications of AI and data science. He/She is dynamic and open-minded.


Please contact Prof. Luc De Raedt.


Go to KU Leuven vacancies (ref BAP-2016-441).