PhD Position: Automated Business Process Improvement via Rule Mining

Institute of Computer Science, University of Tartu, Estonia

University of Tartu's Institute of Computer Science is calling for applications from aspiring computer science researchers to conduct doctoral research within the ERC project The Process Improvement Explorer: Automated Discovery of Business Process Improvement Opportunities (PIX). The overarching goal of this project is to develop algorithms to analyze business process execution data in order to discover process improvement opportunities.

Within this broad project, your PhD project's goal will be to design methods to discover opportunities to alter the resource allocation rules and the decision rules used in a business process, in order to improve its performance with respect to one or more performance measures (e.g. defect rate, cycle time, execution cost). To achieve this, you will apply and enhance existing techniques from the field of rule mining and cost-sensitive learning, and you will combine them with multi-objective optimization techniques in order to build a decision optimization framework and toolset.

You will be part of a cross-disciplinary team, including experts in business process management, process mining, machine learning, and optimization. In the past six years, the group has earned six best paper awards at international conferences (BPM'2013, BPM'2016, ER'2016, ICSSP'2017, RuleML+RR'2017, IPM'2020) as well as one best student paper award, one best dissertation award, and three best demo awards. Further information about the group can be found at

During your PhD, you will receive mentorship from at least two senior staff and one postdoc researcher. You will also have the opportunity to conduct research visits at leading research teams (e.g. at Utrecht University, Technion, University of Melbourne, or WU Vienna).

To apply, you must have a Masters degree in Computer Science, Information Systems, Business Informatics, or a related discipline (or be close to obtaining your Masters). You will need a good foundation in algorithmics and/or machine learning, a basic understanding of information system architectures, and openess to cross-disciplinary research.

Expressions of interest should be sent by e-mail to Marlon Dumas ( by 29 May 2020.