Postdoc in MOOC creation and learning analytics with a focus on process mining

For the European Data Science Academy EU project we are urgently looking for a postdoc (or possibly MSc graduate) that has experience/interest in learning analytics, MOOC creation and process mining. Applications are processed with priority in arriving order, all applications should be submitted through the website. Full vacancy text follows below.

Process Analytics for the European Data Science Academy


The European Data Science Academy (EDSA) is a coordination and support action of the H2020-ICT-15-2014 Big data and Open Data Innovation and take-up program. The aim of the EDSA project is to contribute to capacity-building by designing and coordinating a network of European skills centers for big data analytics technologies and business development. TU/e (Eindhoven University of Technology) is one of the nine partners in this program focusing on topics such as process mining and other types of process analytics. In this context we are looking for a Postdoc until January 31st 2018, starting as soon as possible.

Data Science Centre Eindhoven (DSC/e)

The postdoc will join the Architecture of Information Systems (AIS) group at Eindhoven University of Technology (TU/e). AIS is one of the 28 research groups of the Data Science Centre Eindhoven (DSC/e). DSC/e is TU/e’s response to the growing volume and importance of data and the need for data & process scientists ( DSC/e is one the largest data science initiatives in the Netherlands and therefore involved in the European Data Science Academy (EDSA). The AIS group is one of the leading groups in the exciting new field of process mining ( Process mining techniques focus on process discovery (extracting process models from event logs), conformance checking (comparing normative models with the reality recorded in event logs), and extension (extending models based on event logs). The work resulted in the development of the ProM framework that is widely used in industry and serves as a platform for new process mining techniques used by research groups all over the globe. Moreover, many of the techniques developed in the context of ProM have been embedded in commercial tools. See also

European Data Science Academy (EDSA)

EDSA aims to deliver the learning tools that are crucially needed in order to educate the data scientists needed across Europe. Comprised of a consortium of academic and industry institutions with an excellent track record in professional training in Big Data, open data, and business development; and with strong ties to a wide range of stakeholders in the global data economy, EDSA will implement a cross-platform, multilingual data science curricula which will play a major role in the development of the next generation of European data practitioners. To meet this ambitious goal, the project will constantly monitor trends and developments in the European industrial landscape and worldwide, and deliver learning resources and professional training that meets the present and future demands of data value chain actors across countries and vertical sectors. This includes demand analysis, data science curricula, training delivery and learning analytics. EDSA will provide deployable educational material for data scientists and data workers and thousands of European data professionals trained in state-of-the-art data analytics technologies and capable of (co)operating in cross-border, cross-lingual and cross-sector European data supply chains. TU/e will play an important role in the development of learning analytics based on process mining techniques. Specifically, we will monitor study behavior in detail (with careful consideration of privacy issues) and provide insights into the actual learning experience. All events captured (e.g., watching videos or making online assignments) will be stored in a “process cube”, i.e., a data warehouse holding learning-related events and having dimensions based on student attributes (age, experience, gender, nationality), deployment form, and other course characteristics. The process cube will be used to analyze differences between courses and students, e.g., create process models showing differences between students that pass and those that fail. Next to using process mining for learning analytics, the postdoc will be involved in the development of curricula and learning resources focusing on the interplay between process science and data science. Note for example the MOOC Process Mining Data Science in Action ( The MOOC but also the video lectures at TU/e will be analyzed using process mining techniques.


The postdoc will join the Architecture of Information Systems (AIS) group at Eindhoven University of Technology and focus on the interplay of process mining and data science education. The appointment will be from ‘as soon as possible’, until January 31st 2018.

Function Requirements


We are looking for candidates that meet the following requirements:

  • a solid background in Computer Science or Data Science (demonstrated by Master and PhD degrees);
  • a relevant PhD is expected (ideal candidates have a strong background in process/data mining and an interest in learning analytics);
  • candidates from non-Dutch or non-English speaking countries should be prepared to prove their English language skills;
  • good communicative skills in English, both in speaking and in writing;
  • candidates are expected to realize research ideas in terms of prototype software, so software development skills are needed.

Note that we are looking for candidates that really want to make a difference and like to work on things that have a high practical relevance while having the ambition to compete at an international scientific level (i.e., present at top conferences and in top journals).

Conditions of Employment

Conditions of employment

We offer:

  • a full-time temporary appointment for a period of 36 months;
  • salary in accordance with CAO of the Dutch universities;
  • 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:

The application should consist of the following parts:

  • Cover letter explaining your motivation and qualifications for the position (the letter should show an understanding of process mining and the work done within AIS, see websites such as 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 artifacts developed;
  • Pointer to a copy of the PhD thesis and key publications;
  • Names of at least three referees.

Please apply through the website. Applications via e-mail will not be accepted