Postdoc on the Effects of Social Influence on Driving Behaviour in Urban Settings Delft • TU Delft

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Speeding (driving over the speed limit) is one of the main causes of road fatalities and is detrimental to greenhouse-gas emissions worldwide. While extensive research has been dedicated to understand speeding and its underlying causes, the behavioural / social aspects of speeding are largely unexplored, even though road sharing requires direct social exchanges between drivers. In particular, the effects of social influence or peer pressure on drivers going over the speed limit have been crucially overlooked. The possible reason behind this research gap is the ripple effect in the impact of social influence on speeding behaviour: the surrounding traffic may encourage a driver to go over the speed limit, and as soon as the driver exceeds the speed limit, the driver becomes part of this surrounding traffic for other drivers too and this feedback loop may intensify over time. Studying such a ripple-effect interrelationship requires novel methodologies that can handle endogeneity as well as time-variant choices.

This postdoctoral position will contribute to road safety research by delving into the above complexities and looking at the interrelationship between roadway engineering design, collective and individual speeding behaviour of drivers as well as the spatial / temporal heterogeneity of such behaviour. A small naturalistic driving experiment will be designed and driving data will be collected for a sample of drivers in the Netherlands. A new methodology will the be developed for studying the real-time endogenous speeding behaviour of drivers along several types of urban road configurations in the Netherlands where there is an array of roadway engineering factors (e.g. signalized intersections and varied speed limits) and cultural elements (e.g. speeding and road rage) that have not been considered in previous research.

The successful candidate will work under the supervision of Dr. Amir Pooyan Afghari and at the faculty of Technology, Policy and Management, but will collaborate with a research team from this faculty as well as the faculties of civil and mechanical engineering too. Amir is an assistant professors in transport safety at TU Delft. He has extensively worked in the area of road safety and behavioural modelling.     

• A PhD in transport engineering.
• A master's degree (or equivalent) in transport engineering / data science with a background (BSc) in civil engineering, computer science, mathematics, economics or statistics.
• Applicants with a master's degree in behavioural sciences and with demonstrable econometrics skills can also apply.
• Experience with advanced statistics (advanced econometric models) and probability theories (probability distributions, Bayesian paradigm, etc.).
• Familiarity with machine learning algorithms.
• Coding skills in Python or R.
• Strong conceptual and analytical skills.
• Strong motivation and some experience to undertake research.
• Excellent writing and presentation skills.
• The ability to work both independently and as part of a team.
• Very high level of proficiency in English.

Nice to have:

• Familiarity with road safety / traffic behaviour
• Hands-on experience with machine learning algorithms

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Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

The Faculty of TPM provides an important contribution to solving complex technical-social issues, such as energy transition, mobility, digitalisation, water management and (cyber) security. TPM does this with its excellent education and research at the intersection of technology, society and policy. We combine insights from both engineering and social sciences as well as the humanities. TPM develops robust models and designs, is internationally oriented and has an extensive network of knowledge institutions, companies, social organisations and governments

Click here to go to the website of the Faculty of Technology, Policy and Management.

• Duration of contract is 22 Months.
• A job of 36-40 hours per week. 

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities. The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged. 

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible! The HR unit, Coming to Delft Service, offers information on their website to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands, and expand your (social) network in Delft. A Dual Career Programme is available, to support your accompanying partner with their job search in the Netherlands.  

For more information about this vacancy, please contact Dr. Amir Pooyan Afghari at via de button "Solliciteer nu" op deze pagina..     

Are you interested in this vacancy? Please apply no later than 3 August 2025 via the application button and upload the following documents:

• Motivation letter.
• CV.

You can address your application to Amir Pooyan Afghari.

Please note:

• You can apply online. We will not process applications sent by email and/or post. 
• A pre-employment screening can be part of the selection procedure.
• For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
• Please do not contact us for unsolicited services.