PhD in Statistics and AI for quantitative crowd dynamics modeling

PhD in Statistics and AI for quantitative crowd dynamics modeling

Published Deadline Location
19 Apr yesterday Eindhoven

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Job description

Are you eager to work on a pioneering PhD project at the interface between statistics, artificial intelligence, physics of flowing matter and system identification? Do you enjoy collaborating with researchers from different fields, and combining theory, modeling and experiments? Then this position might be for you!

Whenever our safety and comfort in public areas are at risk because of dense crowds, crowd management failed. Even quite recently, these dysfunctions have cascaded into disastrous accidents. How can this be still acceptable?

This PhD position is part of the 2-PhD project AICrowd: AI-Based Pedestrian Crowd Modelling and Management. This project aims at quantitatively modelling the behavior of human crowds. This is key to surpass our outdated crowd management practices, still based only on back-of-the-envelope size estimates and stewards' experience.

The project aims at a holistic AI framework for crowd modeling and management. This hinges on two recent technological achievements: the capability of performing real-life experimental campaigns and the existence of big crowd dynamics datasets entailing normal and rare conditions. As one of the two PhD candidates in this project, you will be part of the endeavor tacking three outstanding challenges: quantitative stochastic modeling of crowds, scalable model learning, and optimal actuation for experimental design and control.


Eindhoven University of Technology (TU/e)


In this position you will work in the team of dr. Rui Castro (Mathematics/Statistics), under joint supervision of dr. Alessandro Corbetta (Applied Physics/Fluids and Flows) and dr. Maarten Schoukens (Electrical Engineering/Control Systems). A substantial part of your research work will be focused both on the development of sound methods for sequential identification of informative data, leading efficient training of crowd dynamic models, as well as the development of the foundations of adaptive sensing in the general context of system identification. You will be embedded in the Statistics, Probability and Operations Research (SPOR) cluster of the mathematics department, and collaborate closely with experts from the Applied Physics and Electrical Engineering departments, among others.

Conditions of employment

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:
  • Full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months. You will spend 10% of your employment on teaching tasks.
  • Salary and benefits (such as a pension scheme, paid pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labour Agreement for Dutch Universities, scale 27.
  • A year-end bonus of 8.3% and annual vacation pay of 8%.
  • High-quality training programs and other support to grow into a self-aware, autonomous scientific researcher. At TU/e we challenge you to take charge of your own learning process.
  • An excellent technical infrastructure, on-campus children's day care and sports facilities.
  • An allowance for commuting, working from home and internet costs.
  • A Staff Immigration Team and a tax compensation scheme (the 30% facility) for international candidates.


  • PhD
  • Engineering
  • max. 38 hours per week
  • University graduate
  • V32.6575


Eindhoven University of Technology (TU/e)

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De Rondom 70, 5612 AP, Eindhoven

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