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.

 

Project
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 31^st 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 (http://www.tue.nl/dsce/). 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 (www.processmining.org). 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 www.processmining.org.

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 (https://www.coursera.org/course/procmin). The MOOC but also the video lectures at TU/e will be analyzed using process mining techniques.   

Position
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 31^st 2018.

Requirements
We are looking for candidates that meet the following requirements:

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
We offer:

The application should consist of the following parts: