PhD Positions in Data Science at JADS
JADS is a unique collaboration in data science between Eindhoven University of Technology and Tilburg University. At JADS we have the following PhD positions available.
PhD Position available in the area of Data Engineering/Science
JADS, the novel Graduate School on Data Science and Entrepreneurship, is seeking a highly motivated and dedicated PhD candidate to work on exceedingly challenging, innovative, and interdisciplinary research projects at the intersection of data analytics and data engineering.
JADS (www.jads.nl) undertakes innovative, interdisciplinary data science research. We focus on real-world challenges that demand the use of multiple conceptual, methodological and substantive approaches. You will have the opportunity to work in an international environment at the brand new JADS campus in ‘s-Hertogenbosch (The Netherlands) and collaborate with and visit a number of high-profile researchers from universities and research institutes all over Europe.
Candidates should meet the following requirements:
Candidates should be able to work in a collaborative environment with a strong commitment to achieving research excellence.
Interested candidates are requested to send their application to email@example.com including:
The position is available with immediate effect.
PhD Position on Process Mining in Customer Behavior
PhD Position on Process Mining in Customer Behavior - Unique collaboration between BrandLoyalty and the Jheronimus Academy of Data Science.
Faculty Mathematics & Information Science TU/e
Data Science Centre Eindhoven
Consumers can shop for anything, anywhere, anytime and with anyone. Therefore, retailers need to compete on analytics and must analyze customer data carefully. BrandLoyalty is the global leader in providing innovative, incentive-driven loyalty programs designed to drive immediate improvements in retail performance. BrandLoyalty is working together with JADS (Jheronimus Academy of Data Science) to improve its analytical capabilities.
As part of a joint research program we are looking for a PhD student interested in the project “Mining Customer Behavior to Increase the Effectiveness of Loyalty Programs and Promotions (MiCuB)”. The goal of this project is to apply existing process mining techniques to BrandLoyalty’s data and develop new techniques tailored to the analysis of customer behavior.
The PhD working on Process Mining in Customer Behavior will be employed by the AIS research group (http://www.win.tue.nl/ais/) which is part of the Data Science Centre Eindhoven (DSC/e, http://www.tue.nl/dsce/). DSC/e and Tilburg University collaborate in the context of JADS (Jheronimus Academy of Data Science). Together with BrandLoyalty (http://www.brandloyalty-int.com/) a joint research program has been created. Within this research program are three PhD positions, all sponsored by BrandLoyalty, that work towards better analytical capabilities taking advantage of the wealth of (typically anonymized) customer data. To improve customer engagement, process mining is used to get a deep understanding of actual customer behavior. In fact, understanding of customer behavior has never been easier than now. With the rise of mobile, social, and big data technologies, customers are always-connected and can find information in seconds. This enables one to gain much more detailed and direct information on customer behavior.
The “Mining Customer Behavior to Increase the Effectiveness of Loyalty Programs and Promotions (MiCuB)” PhD position will focus on process mining, i.e., the analysis of timestamped customer data.
Process Mining in Customer Behavior
The PhD student will focus on capturing customer behavior in process models. These models will allow us to better understand the behavior and to systematically explore ways of influencing this through promotions, loyalty programs, and mobile applications. The MiCuB project will cover a broad range of questions, such as “Did sales increase?”, “Was the program successful?”, “What has influenced the (un)success?”, “Will the targets be reached?”, “What is the best that could happen?”.
Process mining bridges the gap between traditional model-based process analysis (e.g., simulation and other business process management techniques) and data-centric analysis techniques such as machine learning and data mining. Process mining seeks the confrontation between event data (i.e., observed behavior) and process models (hand-made or discovered automatically). This technology has become available only recently, but it can be applied to any type of operational processes (organizations and systems). The interest in process mining is rapidly rising as it is reflected by the growing numbers of publications, citations and commercial tools (Disco, Celonis, ProcessGold, ARIS PPM, QPR, SNP, minit, myInvenio, Perceptive, etc.). In the academic world, ProM is the de-facto standard (www.processmining.org) and research groups all over the world have contributed to the 1500+ ProM plug-ins available. This platform will be used to first test ideas that could later be implemented in BrandLoyalty's core IT systems
We are looking for candidates for the “Mining Customer Behavior to Increase the Effectiveness of Loyalty Programs and Promotions (MiCuB)” PhD position. The PhD student will join the Architecture of Information Systems group (AIS) at Eindhoven University of Technology (TU/e), which is part of the DSC/e and JADS. Wil van der Aalst will be the promotor and people from both AIS and BrandLoyalty will be involved in the supervision.
The AIS group at TU/e is world leader in process mining research and responsible for ProM and has generated a number of spin-offs. Therefore, the group is well equipped to take on this challenge.
The PhD student will closely collaborate and spend one day a week within BrandLoyalty. The PhD will focus on applying, extending, and developing process mining to the requirements elicited together with BrandLoyalty.
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.
BrandLoyalty will provide its expertise, engineering capabilities, and data for deriving accurate and realistic requirements and will provide opportunities to quickly validate all ideas in a realistic setting.
We are looking for a candidate that meets the following requirements:
The PhD student is expected to:
Please apply by using the 'Apply now' button on top of this page.
The deadline is on February 28th 2017
The application should consist of the following parts:
If you have any questions or if you want to apply for a position, please contact us at firstname.lastname@example.org