Two PhD positions in Human-Centred Artificial Intelligence for Mobility (1.0 FTE) (# of pos: 2)

Utrecht University (UU) is working together with the Nederlandse Spoorwegen (NS ) to translate challenging problems related to passenger mobility into scientific questions. The joint aim is to develop scientific breakthroughs to solve these problems and put them into practice.

Through a coalition formed by Ahold Delhaize, ING, KLM, Philips, and NS, an initiative was established called “Kickstart AI”, based on the conviction that artificial intelligence (“AI”) will become an increasingly decisive part of business operations and with the aim to increase the application level of AI within the Dutch business community and the Dutch AI training capacity. As part of Kickstart AI, NS and UU realized joint appointments, including two 5-year PhD positions.

You will work in an NS team lead by Leo van der Meulen, under the supervision of Professor Judith Masthoff. The positions include 70% research and 30% teaching. Two days per week you will be based at the NS Utrecht office. Three days you will be based in the UU AI & Mobility lab .

Research
The research will focus on human-centred AI to (1) support existing NS customers in making the next-best actions and (2) regain customers by giving them tailored travel inspiration. The two PhD-students will research the following topics:

• Personalized communication: Transparent, adaptive, interactive customer-AI communication, which allows customers to take control of and, consequently, influence their experience positively. AI-induced communication of when what, and how to provide information is central.
• Context modelling: External influences can significantly influence the travel experience and preferences (e.g., concerts and soccer games, weather, and luggage). AI-induced, personalized context models steer when, what, and how these influences are taken into account.

In both topics, ethics and psychological mechanisms are key.

You will build on previous research on AI, personalization, adaptive interaction, and user/context modelling. You will use a mixture of qualitative (e.g., interviews and focus groups), quantitative (e.g., empirical studies), and AI (e.g. data-driven user modelling) methods. Your research will result in both high-quality scientific publications and novel AI-induced NS products to realize real world impact.

Teaching
You will be involved in supporting the preparation and teaching of BSc and MSc courses, offered by the UU Department of Information and Computing Sciences . Furthermore, you will supervise BSc and MSc-student graduation projects, including internships of UU students with NS.