Research Assistant (f/m/d) - PhD position in the field of computer vision and AI for traffic safety and intelligent infrastructure

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.
This is a part-time contract position.
The standard weekly hours will be 31,86 hours.
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

At the Institute for Highway Engineering Aachen, RWTH Aachen University, we develop solutions for safer, more efficient, and more intelligent road infrastructure. Our work combines traffic safety, sensing, and digitalisation.

This position focuses on computer vision and artificial intelligence for the analysis of traffic and infrastructure from camera and multimodal sensor data. Using video, thermal imaging, and other sensor systems, we study vehicles, pedestrians, cyclists, trajectories, interactions, and safety-related events. The aim is to turn complex sensor data into engineering knowledge for traffic safety assessment, infrastructure monitoring, and digital road systems.

We offer a doctoral research position at the interface of infrastructure engineering and artificial intelligence, with access to real traffic data and advanced sensing systems.

The position offers the opportunity to develop original methods and software, publish strong scientific work, and build an independent academic profile. You will contribute to the growth of this research area at ISAC and take part in national and international research activities.

Ihr Profil

Applicants should hold a university degree (master’s degree or equivalent) in computer science, electrical engineering, robotics, transport engineering, or a related field.

We are looking for candidates with strong programming and methodological skills, who are interested in developing their own solutions rather than relying mainly on existing software packages. Strong hands-on programming experience, for example in Python, C++, or similar languages, is essential.

Experience in computer vision, machine learning, or related areas is desirable. Experience in object detection, tracking, trajectory analysis, multimodal sensing, scene understanding, pose estimation, motion analysis, or human-centred visual modelling is an advantage.

The ability to work independently and in an interdisciplinary environment is essential. Very good English skills are required. Knowledge of German is desirable, and willingness to improve German skills is welcome.

Ihre Aufgaben

This position offers the opportunity to carry out doctoral research in computer vision and artificial intelligence for the analysis of traffic participants, traffic scenes, and infrastructure from video and multimodal sensor data. This includes detection, tracking, scene understanding, trajectory reconstruction, interaction analysis, and the automated interpretation of traffic situations.

We are looking for a candidate who is interested in developing original methods and robust processing pipelines for scientific and engineering use, with applications in traffic safety, infrastructure monitoring, and digital road systems.

The successful candidate will contribute to research projects, publish scientific results, and work towards a doctoral degree in this field.

Über uns

RWTH is proud to be certified as a family-friendly university. As part of our Campus Health initiative, RWTH offers a wide range of health, counseling, and prevention services, including university sports. Employees under collective bargaining agreements and civil servants also benefit from a comprehensive continuing education program and the option to purchase a job ticket for convenient commuting.
RWTH is an equal opportunities employer. We welcome and encourage applications from all qualified candidates and make employment decisions without regard to national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is especially committed to supporting the advancement of women in academia. When women are underrepresented in a university unit, preferential consideration will be given to female applicants among candidates of equal merit and professional standing, unless compelling reasons favor another individual.
In keeping with RWTH’s commitment to equality of opportunity, we ask that you do not include a photo with your application.
Please refer to https://www.rwth-aachen.de/applicant-privacy-policy for information about how we collect and process applicant data in accordance with Articles 13 and 14 of the European Union’s General Data Protection Regulation (GDPR).

Besoldung / Entgelt

EG 13 TV-L