Research Assistant/Associate – Doctoral Candidate (f/m/d) in the field of AI-based predictive models for pedestrian behaviour

Weitere Informationen

The successful candidate will be employed under a regular employment contract.
The position is to be filled at the earliest possible date and offered for a fixed term initially for 3 years.
An extension is possible.
The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).
This is a part-time contract position.
The standard weekly hours will be 31,52 hours.
It is an 80% position.
The successful candidate has the opportunity to pursue a doctoral degree in this position.
The salary is based on the German public service salary scale (TV-L).
The position corresponds to a pay grade of EG 13 TV-L.

Unser Profil

The Institute of Highway Engineering (ISAC) at RWTH Aachen University is seeking a motivated PhD student to join our research team. This innovative research aims to significantly improve pedestrian safety at urban intersections by developing AI-based models to predict distracted pedestrian behaviour using trajectory data, visual cues, and real-time simulations.

The project addresses the critical issue of pedestrian safety by creating predictive AI tools that can proactively identify and respond to distracted pedestrian behaviour at road crossings. The research leverages advanced simulation environments, machine learning, and thermal imaging technologies to detect behavioural anomalies indicative of distraction. Ultimately, the developed solutions will be validated through controlled simulations and real-world field tests, contributing to safer urban mobility.

Ihr Profil

• University degree (Master’s degree or equivalent) in Computer Science, Data Science, or closely related fields (candidates with strong computational and analytical backgrounds from related disciplines will also be considered).
• Solid programming skills and willingness to quickly acquire new competencies in machine learning, simulation, and trajectory analysis.
• Interest in applying advanced data analytics and predictive modelling techniques to real-world traffic safety and pedestrian behavioural challenges.
• Excellent command of English; knowledge of German would be beneficial but is not essential.
• Strong motivation to work in interdisciplinary research teams and contribute effectively to project outcomes.

Ihre Aufgaben

• Design and conduct pedestrian simulations and field experiments to systematically generate trajectory data representing distracted behaviours such as irregular walking patterns and hesitations.
• Develop robust machine-learning models capable of accurately predicting pedestrian distraction based on trajectory data and visual indicators from thermal imaging.
• Integrate these predictive models into real-time safety infrastructure systems (e.g., laser projections and dynamic signage).
• Validate developed AI models through simulator-based experiments and controlled real-world field tests.
• Publish high-quality research in peer-reviewed scientific journals, present findings at national and international conferences, and complete a PhD thesis on AI-driven pedestrian behaviour prediction.

Teilzeit-Informationen

It is an 80% position.

Über uns

RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung.

Besoldung / Entgelt

EG 13 TV-L