PHD RESEARCHER IN DECISION MODELING FOR KNOWLEDGE-INTENSIVE PROCESSES

12 February 2019

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Interested?

For more information please contact Prof. dr. Jan Vanthienen, tel.: +32 16 32 68 78, mail: jan.vanthienen@kuleuven.be.

You can apply for this job no later than March 31, 2019 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 March 2019

The research project is funded by the Fund for Scientific Research Flanders (FWO) in cooperation with UGent. The focus of the project will be on Process-Decision Integration for Knowledge-intensive Process Modeling and Discovery. 

The Leuven Institute for Research on Information Systems (LIRIS) has acquired a solid, world-wide recognized reputation in the field of management informatics, as illustrated by the various top publications in high-quality journals, research projects, presentations at well-respected conferences, the frequent organization of scientific events, and the regular editorial activities undertaken. In the area of business informatics, the group has always been a leading research team in Flanders and Belgium. The research team maintains close contacts with other research centers in the faculty, KU Leuven and other universities. LIRIS cooperates with leading international academic research centers in business information systems.
The LIRIS group has extensive links with a network of national and international industry partners, serving either as research sponsors or facilitators for data provisioning and research validation. This cross-fertilization between fundamental research and industry practice allows to conduct research according to the domain’s motto: rigor and relevance.

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Project

The research project is funded by the Fund for Scientific Research Flanders (FWO) in cooperation with UGent. The focus of the project will be on Process-Decision Integration for Knowledge-intensive Process Modeling and Discovery. 
As a PhD-student, you are expected, next to your main research tasks, to participate in seminars and conferences, to enroll in the PhD program of the Faculty of Economics and Business, and to perform a limited amount of educational duties (e.g. supervising student master's thesis). For more information about the PhD programme in Business Economics, see https://feb.kuleuven.be/resear...

Profile

Candidates preferably have a master's degree in Business and Information Systems Engineering, Business Engineering, Informatics, Computer Science, Artificial Intelligence, or Statistics. Excellent (honors-level) results in prior studies are required. Candidates must satisfy the prerequisites for admission to the PhD programme of our faculty (https://admin.kuleuven.be/rd/doctoraatsreglement/en/phdregulation-feb). In particular a GRE or GMAT result above the 75th percentile on the quantitative part and an English TOEFL (minimum score 575 paper-based, 233 computer-based, 90 internet-based), or IELTS (minimum score 7) test, both not older than 5 years are required to enter the program. In addition, we require:

  • Solid programming skills. Knowledge of business process modeling, process mining, knowledge representation techniques is a plus. 
  • Ability to work efficiently in a research setting, i.e. be able to investigate new research questions and solutions.
  • Strong mathematical background.
Offer

We offer a fulltime employment as a doctoral scholar for 1 year, renewable till max. 4 years after positive evaluation. You will work under the supervision of Prof. Jan Vanthienen. 
You will be located at the Leuven Institute for Research on Information Systems (LIRIS) at KU Leuven (Leuven, Belgium). You will find a dynamic and pleasant working environment in this research group that is actively involved in scientific research at the highest international level in different domains such as business intelligence, data mining, decision modeling, conceptual modelling, model-driven engineering, and smart learning environments. Research projects in these domains are focusing both on fundamental research as on applied research. For more information, check our group's home page.