You should have a strong interest in (a subset of) the areas of information systems, machine learning, statistics, and/or data science. You should be passionate about growing in a research setting and to become an independent researcher.
You should preferably hold a Master’s degree in Operations Research, Business Engineering, Statistics, Applied Mathematics, Computer Science, or equivalent. An appropriate command of written and spoken English is a requirement, and experience with at least one programming language is an asset. Students that are currently in the final year of their Master’s are especially encouraged to apply.
Excellent (honors-level or better) results in prior studies are required. Candidates must satisfy the prerequisites for admission to the PhD programme of our faculty. There is a strict requirement that you can demonstrate academic excellence (at least honours level) for at least two years. For international candidates 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:Processes are the drivers of most information systems. During their execution, they produce vast amounts of data in the form of event logs related to the activities of their users, such as loan application officers, clients purchasing, doctors supporting patients, and so on. Our research focuses on the analysis of these event logs by creating data-driven predictive (e.g. will a loan get accepted?) and prescriptive (e.g. what treatment works best to have more successful loan applications?) techniques using machine and deep learning including forecasting models, neural networks, (deep) reinforcement learning, and causal inference.
The goal of this project is to shift from working from specific perspectives (e.g. the customer drives my process) to multi-perspective analysis of event logs, taking into account all objects in an event log and system to adhere to the object-centric process modelling paradigm (e.g. a loan application contains several loan officers, customers, forms, loan products, and so on). In parallel, we envision to adapt a system-wide perspective to capture the impact of the global behaviour of, e.g., the resource allocation on individual objects such as a single loan application being delayed because of understaffing. By doing so, it becomes possible to build stronger predictive and prescriptive applications which will have a more accurate view of the factors influencing their outcome.The Research Centre for Information Systems Engineering (LIRIS) at KU Leuven (Brussels & Leuven, Belgium) is a dynamic research group that is actively involved in scientific research at the highest international level in various fields such as data science, business process management, conceptual modelling, model-driven engineering. The research group also has a strong focus on technology-enhanced education and seeks to support its educational practice through the development of didactic tools and learning analytics. For more information, see the home page of our group.We offer employment as a full-time doctoral scholarship for 4 years at KU Leuven. You will work under the supervision of Prof. Johannes De Smedt and Prof. Jochen De Weerdt.
You will be located at the Research Centre for Information Systems Engineering (LIRIS) at KU Leuven (Brussels & Leuven, Belgium)