[DL] PhD Position on Business process discovery and alignment @FBK and Univ. of Bozen-Bolzano

Chiara Ghidini ghidini at fbk.eu
Thu Jun 8 21:32:46 CEST 2017


One four-year PhD grant on Business process discovery and alignment is offered by the faculty of Computer Science of the Free University of Bozen-Bolzano in Italy jointly with the Process & Data Intelligence research unit at Fondazione Bruno Kessler, Trento, Italy, where most of the research activities will be conducted. The grant amounts to 68,000 €; for research visits abroad the grant can increase up to 50%. Substantial extra funding is available for participation to international conferences, schools, workshops, research visits.

	The deadline for applications is 3 July 2017.
	For more info, the call, and applications look at: 
	www.unibz.it/en/faculties/computer-science/phd-computer-science <http://www.unibz.it/en/faculties/computer-science/phd-computer-science>
	The language of the PhD program is English. 

Topic description: Process discovery techniques return process models that are either formal (precisely describing the possible behaviors) or informal (merely a “picture” not allowing for any form of formal reasoning). Formal models are able to classify traces (i.e., sequences of events) as fitting or non-fitting. Most process mining approaches described in the literature produce such models. This is in stark contrast with the over 25 available commercial process mining tools that only discover informal process models that remain deliberately vague on the precise set of possible traces. There are two main reasons why vendors resort to such models: scalability and simplicity. Within this PhD program, the candidate will have the chance to combine the best of both worlds: discovering hybrid process models that have formal and informal elements. Achieving this task requires dealing with several fascinating challenges as, for example, (i) the capability to work with formal and informal representations; (ii) the capability to envision new alignment strategies between execution traces and hybrid models; (iii) the capability to implement scalable solutions.
The work will put together theoretical and methodological aspects, including for example the problem conceptualization and representation, as well as implementation and optimization ones, aimed at the development of process mining and alignment tools.

About us: The Free University of Bozen-Bolzano and Fondazione Bruno Kessler are located 50 KM apart in one of the most fascinating European regions, the Dolomites. The young Free University of Bozen-Bolzano has already established itself as an important research institution, both in Italy and abroad. According to the Times Higher Education World University Rankings 2017, the university is the tenth world’s best small university, is the fifth best among all the Italian Universities with computer science departments, and it is the second best young Italian University. Fondazione Bruno Kessler is an internationally well-known research center, whose information technology department ranks first among the Engineering and Information Science research centers in Italy. 
The Process & Data Intelligence research unit (http://pdi.fbk.eu <http://pdi.fbk.eu/>) is a young and internationally well known research group focused on the interplay between formal (and especially logic-based) representations of knowledge and data driven representations of knowledge, with particular emphasis on Process-aware systems and semantic web based systems. The PhD will be conducted under the joint supervision of Dr. Chiara Ghidini and Prof. Wil van der Aalst, in his capacity as visiting scholar at Fondazione Bruno Kessler. 

To get in contact with the PDI Research unit and discuss about the opportunities of this call contact Chiara Ghidini at ghidini at fbk.eu <mailto:ghidini at fbk.eu>.

To know more on the topic have a look at: 
Wil M. P. van der Aalst, Riccardo De Masellis, Chiara Di Francescomarino, Chiara Ghidini:
Learning Hybrid Process Models From Events: Process Discovery Without Faking Confidence. 
In Proc. of the 15th International Conference on Business Process Management (BPM2017). 
To appear. Long version at https://arxiv.org/abs/1703.06125 <https://arxiv.org/abs/1703.06125>.  
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