The Institute for Road Science Aachen stands for a sustainable and digital transport infrastructure. As a research institution, we therefore rely on the development and use of modern technologies and processes in the field of road infrastructure. Accordingly, the institute is currently focusing on research into new methods of condition assessment and forecasting, including digital technologies such as Building Information Modeling (BIM). Complex database structures, machine learning algorithms and image processing analysis methods are used.
Independent work on difficult research tasks:
Acquire, create, and manage data from a range of sources such as industry, government, and labs to support projects in material science, road safety, and related fields.
Conduct data analysis using statistical and artificial intelligence techniques to provide actionable scientific insights.
Apply BIM techniques and contribute to the development of digital twins related to road infrastructure.
Design and implement data acquisition methodologies, with a focus on pavement properties, environmental factors, and accident data.
Engage in interdisciplinary research, contributing to grant writing and project management.
Publish research findings in peer-reviewed journals and collaborate within and outside the institute for broader interdisciplinary work.
Help in Master and PhD student supervision and lecturing
University degree (Master or equivalent) in data science, information technology, building informatics, computational engineering, or a related subject and a completed PhD in a relevant field (Data Science, Civil Engineering, Material Science, etc.).
Proficiency in Python, SQL, noSQL, Ontology, and Big Data. Experience in data science is essential.
Knowledge of BIM methods, Autodesk Revit (or any visualisation tool), and standard exchange formats like IFC, CityGML.
Interest in complex analysis methods such as machine learning, predictive analytics, and computer vision.
Good programming knowledge of common languages (Python, C++, etc.) and experience in relevant software libraries (PyTorch, Keras, Tensorflow, OpenCV, etc.) is an advantage.
Business fluent German will be considered an advantage.
Die Einstellung erfolgt im Beschäftigtenverhältnis.
Die Stelle ist zum nächstmöglichen Zeitpunkt zu besetzen und befristet auf zunächst ein Jahr.
Eine Weiterbeschäftigung von zwei Jahren geplant.
Die befristete Beschäftigung erfolgt im Rahmen der Befristungsmöglichkeiten des Wissenschaftszeitvertragsgesetzes.
Es handelt sich um eine Teilzeitstelle.
Die regelmäßige Wochenarbeitszeit beträgt 26,55 Stunden.
Eine Promotionsmöglichkeit besteht.
Die Eingruppierung richtet sich nach dem TV-L.
Die Stelle ist bewertet mit EG 13 TV-L.
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 14 TV-L