Assistant Professor AI-based Real Time Transport Supply-Demand Management

• Are you eager to develop the new research field of AI- based management system which in real time gives advice to travelers, transport providers and network managers to ultimately develop an efficient balance between transport demand and supply?
• Is your next dream move an Assistant Professor role within the research field of AI-based Real Time Transport Supply-Demand Management?
• Are you challenged by teaching Bachelor and Master level students? One where you're expected to write research proposals to acquire fund and publish in high quality journals and be member of committees within faculty and/ or university?
• Are you passionate about the topics of AI-based transport supply-demand management?

Position context

Housten, we have a challenge. An extremely large amount of data is available regarding real time (private and public) vehicle positions, aggregate traffic conditions, real time states of infrastructure, route planning recommendation (to drivers who use such system), position of sharing services in the network, availability of parking areas, accidents and in the future information about the presence of Autonomous Vehicles in the network.

To overcome the challenges cities are facing, such as emission and congestion, it is vital that the substantial amount and diversity of data to be collectively and simultaneously used to optimize the usage of services and infrastructure by giving the right people, right types of advice at right times and right places and update the system in real time given citizens' reaction (to the recommendation).

This reduces pressure on infrastructure (roads and parking for example), and allows valuable land in city areas to be better used for green and/or community-based facilities. The challenge therefore necessitates a system which optimizes the traffic network by collecting real time information, and providing recommendations to the drivers (as close to their preference as possible, whilst respecting their temporal and spatial constraints) in terms of mode choice, route choice, destination choice, departure time and activity duration.

The system also enables the traffic infrastructure to be adjusted in real-time to maximize the efficiency of traffic. In the future, when AV would be part of the urban fleet (mixed fleet), having such a system in place which encompasses the real time information of manual cars, AV and states of infrastructure, would guarantee higher level of safety by communicating information to relevant parties (drivers, AV, infrastructure and transport service providers).

As an assistant professor, you will contribute to achieving the educational and research objectives of the chair of urban planning and transportation group, within the unit Urban Systems and Real Estate (USRE). Part of your task is supervising of BSc, MSc and co-supervising of PhD students. You will contribute in teaching of courses at Bachelor and Master level. You are expected to write research proposals to acquire fund and publish in high quality journals and be member of committees within faculty and/or university.

Requirements:

We offer a stimulating and ambitious educational and research environment and are looking for candidates with the following qualifications:

• You hold an MSc Degree in Engineering and a PhD Degree in the field of data science,  or computer science minoring in transportation or a degree in transportation engineering with rich knowledge in deep learning and programming.
• You have demonstrated your research skills by means of publications in reputed journals and conference proceedings.
• You have an affinity with deep learning algorithms,  geospatial information systems (GIS) and have high expertise in Python and R.
• You have gained international experience and collaborated with international thought leaders in academia on the vacancy topic.
• You can create a vibrant and effective learning environment and have the ability to motivate students both in research-based and challenge-based types of education (academic proficiency and design and engineering attitude).
• You have an excellent and broad international network in academia and industry to acquire research grants.
• You have an affinity with engineering and planning applications in the built environment and a creative mind in finding new solutions.
• You have a good command of English, both orally and in writing.
• You are a team player by nature, but able to work collaboratively as well as independently.

Salary Benefits:

A meaningful job in a dynamic and ambitious university, in an interdisciplinary setting and within an international network. You will work on a beautiful, green campus within walking distance of the central train station. In addition, we offer you:
 

• A Tenure Track of five years with the prospect of becoming an Associate Professor.
• The opportunity to focus your career on education, research or impact. You can develop your personal ambitions and objections within the strategic objectives of the university.
• Salary in accordance with the Collective Labour Agreement for Dutch Universities, scale 11 (min. €4.332,-max. € 5.929,-).
• A year-end bonus of 8.3% and annual vacation pay of 8%.
• High-quality training programs for academic leadership and teaching.
• An excellent technical infrastructure, on-campus children's day care and sports facilities.
• Partially paid parental leave and an allowance for commuting, working from home and internet costs.
• A Staff Immigration Team is available for international candidates, as are a tax compensation scheme (the 30% facility) and partner career support.

38 hours per week

De Rondom 70