Project background and industry involvement
This PhD project will be conducted in collaboration with KPN, a leading telecommunication firm in the Netherlands. Therefore, the practical implications of this research need to be articulated and communicated during the project.
KPN is moving away from a static infrastructure towards a more dynamic infrastructure with streaming data, in which KPN’s Data Services Hub (DSH) will be instrumental. This new set-up of the technological infrastructure has an enormous impact on KPN. Handling large swaths of streaming data does not only require a novel technological infrastructure, but it also has great impact on the organization. First, streaming data typically requires dedicated data mining techniques. Second, streaming data requires different ways of interacting with the customers and employees with more emphasis on shared man and machine decision-making. Third, with streaming data, KPN will add more digital services in their portfolio. This requires new business models to monetize the data. Last, but not least, streaming data typically requires a different way to govern and manage the data. The technical platform should be aligned with KPN’s portfolio of business models and management methods.
This project focusses on the soft side of streaming data technologies in general and DSH in particular.
Increasing numbers and connectedness of sensors, devices and software systems is equally mimicked by the increasing interdependencies between the involved individuals and organizations that make up the network. These are imprinted in business models and are shaping business ecosystems. Similar challenges are observed in the internal processes, starting from aligning different teams to data-driven mindset(s) and new business development.
In this research, we will search for optimal configurations of technology, business models and organizational models, involving the following questions: Which use cases of the DSH are likely to be successful? Which use cases of DSH are likely to have positive (or negative) spill-over effects due to the business and organizational aspects? What are the interdependencies between on-line machine learning algorithms, business models, and organizational models, and how should these be developed and managed? How can we add value to the customers? How should we organize the services on such platforms as DSH accordingly? What skills do we need to be successful and what are the requirements of the organizational culture?
In this research we will be working with the existing and potential business and use cases of the DSH. These use cases are subdivided into three potential categories; internal use cases, external uses cases and 5G-experiments. In each of these use cases we will study; a) the on-line machine learning algorithms, b) the organizational model and c) the business model in detail. Here we try to uncover the soft and hidden secrets of successes and failures of working with machine learning applied to streaming data.
The research will be conducted under supervision of dr. Ksenia Podoynitsyna.
Our ideal candidate wants to build the bridges between social sciences on one side, and mathematics, statistics, and computer science on the other side. While a healthy understanding of mathematics & statistics is required in this project, it is more important to have a strong understanding of the various strands of social sciences /entrepreneurship and a capability to translate these theories and ideas to statistical and analytical models.
The successful candidate is expected to:
The PhD student will be appointed at JADS via an employment at Eindhoven University of Technology (TU/e) or at Tilburg University (TiU).
The Jheronimus Academy of Data Science (JADS) constitutes a unique concept in which an integrated approach to Data Science is created by combining the exact sciences of the Eindhoven University of Technology, with the social sciences of Tilburg University. JADS boasts three campuses at Tilburg, Eindhoven and Den Bosch. JADS Campus Den Bosch revolves around research, education and valorisation on data entrepreneurship.
More information about JADS can be found at www.jads.nl.
Do you recognize yourself in this profile and would you like to know more? Please contact dr. Ksenia Podoynitsyna (E: K.S.Podoynitsyna[at]tue.nl) in case of further questions regarding this project.
For information about terms of employment, please contact HR services, hr[at]jads.nl or +31 40 247 3699
We invite you to submit a complete application by using the 'apply now'-button on this page. The application should include a:
If you are interested, we invite you to apply immediately, and not later than September 1, 2020. We plan to have the first interviews in the third week of September 2020.
You can only apply online.
!!Mind that you will be redirected to the website of Tilburg University. If this is not the case (could happen when you have a registered account on the TU/e website) please go to the vacancy website of TiU. Applications via the TU/e website will not be taken into consideration.
The starting date of this position is as soon as possible.
The Jheronimus Academy of Data Science, or ‘JADS’ is a high-level hotspot where researchers, data science students, start-ups, scale-ups and experts of industry collaborate in developing cutting-edge research to real-world solutions. JADS is all about creating added value and impact with its combination of data science and entrepreneurship. JADS constitutes a unique concept in which an integrated approach to Data Science is created by combining the exact sciences of the Eindhoven University of Technology, with the social sciences of Tilburg University. JADS boasts three campuses at Tilburg, Eindhoven and Den Bosch.
The JADS Campus at the Mariënburg convent in Den Bosch revolves around research, education and valorization on data entrepreneurship.We offer:
Additionally, the Mariënburg Campus, which is the main location of JADS, is located in a historic and beautiful former convent in the heart of the medieval city of ‘s-Hertogenbosch and within walking distance of the central train station.
In short, JADS is a buzzing space where education, research and business meet data science at the center stage.