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

Job Description

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 This is key to surpass our outdated crowd management practices, still based only on back-of-the-envelope size estimates and stewards' experience.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 analytics. 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 candidates in this project you will be part of the endeavor tacking three outstanding challenges: quantitative stochastic modeling of crowds, maximization of data-informativity, and optimal actuation for experimental design and control.

You will work in the team of dr. Alessandro Corbetta (Applied Physics/Fluids and Flows), under joint supervision of dr. Marteen Schoukens (Electrical Engineering/Control Systems) and dr. Rui Castro (Mathematics/Statistics). A substantial part of the research will focus on developing a AI-based system identification approach to achieve quantitative, statistically accurate, models for crowd flows. Your research will impact both on crowd physics as well as in the fields of mathematical modeling, AI, and system identification. You will get the chance to work with unique real-time high-resolution crowd tracking data from state-of-the-art facilities. This project will be embedded in the Crowdflow research group and will allow you to closely collaborate with experts of all departments of the university.

Besides research you will also contribute to education within the department. Apart from supervising BSc and MSc students in their research projects, other assistance in education, e.g. in bachelor courses, is usually limited to around 5% of your contract time.

https://www.youtube.com/watch?v=iEOUgUKFMTs&t=1s&ab_channel=UniversiteitvanNederland

• A master's degree (or an equivalent university degree) in applied mathematics, (computational) physics, electrical engineering.
• Experience in theoretical/numerical modelling, e.g. in fluid dynamics/soft-matter physics/system identification.
• Strong affinity with complex programming efforts and excellent knowledge of python.
• Knowledge of other programming languages will be considered a plus.
• Self-motivated, enthusiastic, proactive, goal-oriented.
• Eager to learn.
• Good organization and communication skills.
• Fluent in spoken and written English.
• Journal/conference publications will be considered and additional advantage.

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 (min. €2,541 max. €3,247).
• 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.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.