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 to 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? What are the optimal roles for KPN in different ecosystems resulting from the European Data Strategy? Examples of horizontal ecosystems are GAIA-X, GSMA, IDSA and ETNO, while vertical ecosystems include Health, Agriculture and City among others.
In this research we will be working with the existing and potential business and use cases of the DSH. 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 employed at Eindhoven University of Technology.
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 in Den Bosch revolves around research, education and valorisation on data entrepreneurship.
Please contact dr. Ksenia Podoynitsyna in case of further questions regarding this project. When applying, please provide a motivation letter, a detailed CV, and the grades list for both BSc and MSc degrees. A proof of English proficiency (TOEFL/IETS) is very much appreciated.
Application can only be done through the online portal of the TU/e (see button below). Applications via regular email will not be taken into consideration. The deadline for submitting your application is April 1, 2021.
At JADS, you work in an ambitious team of professionals to meet the challenges of tomorrow together. We do cool stuff, that matters. We provide talent opportunities for both scientific staff and support staff. JADS is a human-centered organization; we pay attention to your personal development and value a good work-life balance.