PhD Position on Automated Process Improvement

Institute of Computer Science, University of Tartu, Estonia

The Institute of Computer Science at University of Tartu 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 goal of this project is to develop algorithms to analyze business process execution data in order to discover optimal sets of process improvement opportunities, including changes in the execution order of activities, partial automation of activities, changes in resource allocation rules, and changes in decision rules, which may collectively increase operational efficiency and quality. Further information about the PIX project can be found at: https://sep.cs.ut.ee/Main/PIX

Within the broader PIX project, you will focus on developing an algorithmic framework to systematize the "seven wastes" of the Toyota system. Specifically, you will combine graph algorithmics, machine learning, and combinatorial optimization techniques, to analyze business process execution logs with the aim to systematically identify occurrences of different types of wastes as well as optimal combinations of decisions and actions to reduce the impact of these wastes.

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 five best paper awards at international conferences (BPM'2013, BPM'2016, ER'2016, ICSSP'2017, RuleML+RR'2017) as well as one best student paper award and two best demo awards. Further information about the group can be found at https://sep.cs.ut.ee/

During your PhD, you will receive mentorship from at least two senior staff and one postdoc researcher, and will be given the opportunity to undertake research visits in 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 (firstname.lastname@ut.ee). Expressions of interest will be examined on a first-come first-serve basis until 10 June 2019. The expected starting date is 1 September (negotiable).