Research Assistant/Associate (f/m/d) artificial intelligence and digital twin technologies for road 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.
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 31,86 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 infrastructure engineering, sensing, artificial intelligence, and digitalisation.
This position focuses on artificial intelligence and digital twins for road infrastructure monitoring. Using sensor data, digital models, experimental data, and field measurements, we study how road infrastructure responds to traffic, climate, and use over time. The aim is to turn complex infrastructure data into engineering knowledge for monitoring, maintenance planning, and digital road systems.

Ihr Profil

Applicants should hold a university degree, preferably a master’s degree (or comparable), in artificial intelligence, computer science, data science, electrical engineering, robotics, applied mathematics, physics, engineering informatics, civil 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, MATLAB, C++, or similar languages, is essential.
Experience in artificial intelligence, machine learning, signal processing, time-series analysis, data fusion, inverse modelling, optimisation, digital twins, digital infrastructure models, infrastructure monitoring, or decision-support systems is desirable.
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 artificial intelligence and digital twins for road infrastructure. The work focuses on the analysis, interpretation, and integration of infrastructure data into digital models that can support monitoring, assessment, and decision-making.
This includes signal processing, time-series analysis, data fusion, inverse modelling, condition assessment, anomaly detection, and the automated interpretation of infrastructure behaviour under real operating conditions.
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 intelligent infrastructure, digital twins, road monitoring, and predictive maintenance.
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