Two PhD positions on Process Mining in Logistics

In the context of the joint research program between the Data Science Centre Eindhoven (DSC/e) and Vanderlande, we are looking for two PhD students interested in “Process Mining in Logistics Processes and Automated Material Handling Solutions”.

Function PhD-student
Departments Department of Mathematics & Computer Science
Institutes and others Data Science Center Eindhoven
Impuls-vacancies (promovendi) Yes
FTE 1,0
Date off 31/01/2016
Reference number V32.2446

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Job description

Context

The Data Science Centre Eindhoven (DSC/e) is TU/e’s response to the growing volume and importance of data and the need for data & process scientists (http://www.tue.nl/dsce/). Vanderlande is the global market leader in baggage handling systems for airports and sorting systems for parcel and postal services, and also a leading supplier of warehouse automation solutions (http://www.vanderlande.com/). Vanderlande recognizes the emerging trend of more data driven business models and addressed ‘big data’ a key topic on the technology roadmap. Therefore, under the umbrella of the “Data Science Impuls” program, the DSC/e and Vanderlande joined forces in a research project with the aim of bringing holistic fact-based process analytics to logistics processes and automated material handling solutions. This by providing automated insight in process flows, process performance and bottlenecks to obtain improvement information in an efficient way (historical as well as real time).

Process Mining in Logistics

The dynamics of logistics processes are notoriously difficult to analyze. Where classical process mining focuses on analyzing the processing of information associated to a specific unique case, logistics deals with physical objects that are grouped and processed together with other physical objects in one process at one or more physical locations, then distributed and later on re-aggregated with other physical objects in another process at other physical locations. As a consequence, processes reveal a multi-dimensional nature when looking at the performance of flows across networks of logistics. In essence, logistics deals with numerous processes, cases, and objects that interact with each other in a multi-dimensional fashion making it impossible to pick a single appropriate viewpoint on the data for analysis and improvement.

The goal of the joint research project of DSC/e and Vanderlande is to lift process mining to this multi-dimensional space, and to allow analyzing logistics processes and systems from all relevant angles and viewpoints. By having thorough and fast insight into logistics and business processes, improvements can be found, predicted, and implemented at Vanderlande delivered logistics solutions. We aim to achieve this lift for the entire process mining spectrum

  • from appropriate data logging and event data extraction techniques from logistics systems
  • and appropriate conceptual modeling of logistics processes and systems
  • via process discovery and process replay techniques for multi-dimensional event data
  • for online and offline deviation detection and process comparison,
  • to predictions of process outcomes and online recommendations based on event data.

Positions

The project has two PhD positions within the joint research project of DSC/e and Vanderlande. The two PhDs will join the Architecture of Information Systems group (AIS) at Eindhoven University of Technology (TU/e) and be supervised by Dirk Fahland and Wil van der Aalst (TU/e). In addition, the two PhDs will closely collaborate and spend significant time within Vanderlande. In this context, the two PhDs will focus on applying, extending, and developing process mining to the requirements elicited together with Vanderlande. In particular, the results obtained in the project shall both be implemented in software prototypes for validation and research as well as disseminated in trainings. The two PhDs are expected to closely collaborate on the project and solve the upcoming challenges jointly from different angles.

Vanderlande provides its expertise, engineering capabilities, and data for deriving accurate and realistic requirements for various kinds of logistics solutions and problems as well as the opportunity to quickly validate all ideas in a realistic setting. The Architecture of Information Systems group (AIS) of TU/e provides its long running expertise and experience across all challenges of process mining in general and artifact-centric process mining specifically. Job requirements

Requirements

We are looking for candidates that meet the following requirements:

  • a solid background in Computer Science, Data Science, or Mathematics (demonstrated by a relevant Master);
  • ideal candidates have a strong background in process/data mining, logistics, and/or databases (in particular data modeling and query construction);
  • have a strong interest in data science research;
  • have the ability to realize research ideas in terms of prototype software, so software development skills are needed.
  • are highly motivated, rigorous, and disciplined when developing algorithms and software according to high quality standards;
  • good communication skills in English, both in speaking and in writing (candidates from non-Dutch or non-English speaking countries should be prepared to prove their English language skills);
  • possess good communication capabilities and be an efficient team worker.

PhD students are expected to:

  • perform scientific research in the domain described
  • collaborate with other researchers in this project
  • present results at (international) conferences
  • publish results in scientific journals
  • participate in activities of the group and department, at both sites
  • assist in teaching undergraduate/graduate courses
  • participate in doctoral training on relevant topics
  • be willing to work at two locations (TU/e campus and at Vanderlande)
  • provide training to internal specialists at Vanderlande

Conditions of employment

We offer:

  • A full time temporary appointment for a period of 4 years, with an intermediate evaluation after 9 months;
  • A gross salary of € 2.173 per month in the first year increasing up to € 2.778 in the fourth year;
  • Support for your personal development and career planning including courses, summer schools, conference visits etc.;
  • A broad package of fringe benefits (e.g. excellent technical infrastructure, child daycare and excellent sports facilities).

Information and application

More information

  • For more information about this position contact Dr. Dirk Fahland (Assistant Professor), e-mail: d.fahland@tue.nl or by telephone: +31 40 247 4804
  • For more information about the employment conditions contact drs. Charl Kuiters (HR advisor), e-mail: pzwin@tue.nl or by telephone: +31 40 247 2321.

Application

The application should consist of the following parts:

  • Cover letter explaining your motivation and qualifications for the position (the letter should also show an understanding of process mining and the work done within AIS, see websites such as www.processmining.org and the book “Process Mining: Discovery, Conformance and Enhancement of Business Processes”);
  • Detailed Curriculum Vitae;
  • List of courses taken at the Bachelor and Master level including marks;
  • List of publications and software artefacts developed (if applicable);
  • Names of at least three referees.

Please apply by using the 'Apply now' button on top of this page before January 31st, 2016.

Applications via e-mail will not be accepted.