Assistant/Associate Professor position in AI-Driven Transport Modelling and Prediction
Would you like to advance data-driven transport modelling, planning, and prediction in a multidisciplinary team? Do you like to teach and want to shape the next generation of transportation engineers? We are looking for an excellent, enthusiastic scholar to join our Transport Studies group. This group belongs to the Civil Engineering and Management (CEM) department at the Faculty of Engineering Technology.
Research in the Transport Studies group focuses on interactions between smart mobility and digitalisation, transport infrastructure, land-use and behaviour, and its societal impacts (including equity, safety, climate). We take an interdisciplinary and multidisciplinary perspective on transport and collaborate with researchers in the Netherlands and abroad from various disciplines (including industrial engineering, human factors, computer science, geography, urban planning, healthcare technology, and operations). We conduct ground-breaking research on these issues in different national and international projects. As an Assistant or Associate Professor, you will conduct research, acquire external research funding, supervise PhD students, and teach and coordinate courses at the Bachelor and Master’s level. Join our team and strive to broaden our research portfolio!
The challenge
There is huge potential to benefit from the increasing availability of (big) data in the transportation domain. A wide range of sensors, part of mobile phones, vehicles, and Internet of Things devices, generate data continuously. Data science technologies, spatial data, and geo-visualization techniques open unprecedented opportunities to better explain and predict travel patterns. Artificial Intelligence (AI)-driven modelling and prediction has the potential to reshape urban mobility. AI can help operators in transport planning, demand prediction, real-time traffic management, and the optimization and maintenance of traffic and transport systems. AI can also offer travellers opportunities for better travel planning and travel experiences by mobile apps and virtual assistants.
As an Assistant/Associate Professor you will:
- carry out innovative research in the field of data-driven and Artificial Intelligence (AI)-driven modelling, planning and prediction
- develop ground-breaking research projects in close collaboration with colleagues and the industry.
- improve your home-based specific expertise and develop an interdisciplinary research line.
- acquire external research funding and build our research and teaching ecosystem
- teach and coordinate courses in our Bachelor programme Civil Engineering and Master track Transport Engineering and Management which is part of the Master programme Civil Engineering and Management
- supervise students in their graduation assignment
- contribute to the supervision of PhD candidate(s).
Information and application
Please submit your application before October 31, 2025, by clicking the “Apply now” button.
Online interviews will be scheduled in weeks 45 and 46 (between November 6-14, 2025).
Follow-up in-person interviews will be arranged in weeks 48 and 49 (November 24 to December 5, 2025).
Make sure you upload the following additional documents in PDF format, stating the vacancy number 2242:
- Motivation letter describing your research interests, personal qualifications (research and education), and motivation to apply (max. 3 pages)
- Curriculum vitae with a list of publications
- A sample publication
- The names and addresses of three possible referees.
Screening is part of the selection procedure
Additional information about this position can be acquired from Prof. dr. Karst Geurs, chair the application committee and head of the Transport Studies Group, (email k.t.geurs@utwente.nl or phone +31 53 489 1056).
About the organisation
The Faculty of Engineering Technology (ET) engages in education and research of Mechanical Engineering, Civil Engineering and Industrial Design Engineering. We enable society and industry to innovate and create value using efficient, solid and sustainable technology. We are part of a ‘people-first' university of technology, taking our place as an internationally leading center for smart production, processes and devices in five domains: Health Technology, Maintenance, Smart Regions, Smart Industry and Sustainable Resources. Our faculty is home to about 2,900 Bachelor's and Master's students, 550 employees and 150 PhD candidates. Our educational and research programmes are closely connected with UT research institutes Mesa+ Institute, TechMed Center and Digital Society Institute.
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