Academic Employee (f/m/d) „EU Project ENGAGE - Off-highway Road Quality Maintenance for Autonom...

Helmholtz Association of German Research Centres; Deutschland; Vor Ort; EUR 30.000 - 40.000; Teilzeit

Zusammenfassung

A leading research organization in Germany is offering a part-time position focused on mobile working machines and sustainability. The role involves developing methods for evaluating terrain accessibility using advanced technologies and contributes to engineering education through a doctoral thesis. The ideal candidate will collaborate with tech leaders and academic groups to foster the next generation of engineers.

Qualifikationen

• Cutting-edge expertise in AI and robotics.
• Ability to work with 3D digital environment maps.
• Interdisciplinary expertise in machine learning and construction processes.

Aufgaben

• Develop advanced methods for evaluating terrain accessibility.
• Train and educate future engineers in mobile working machines.
• Contribute to the dissemination of project outcomes through digital platforms.

Jobbeschreibung

Area of research

Other

Part-Time Suitability

The position is suitable for part-time employment.

Starting date

14.10.2025

Job description

Mobile working machines (MWM) are critical to industries like construction, mining, and agriculture and key to Europe’s sustainability and productivity goals. To meet rising demands for green, autonomous, and digital solutions, the ENGAGE network brings together top machine manufacturers (Volvo CE, Liebherr, Ponsse, AGCO), tech leaders (Bosch, Bosch Rexroth, Novatron, GIM Robotics), and six leading academic groups across Europe (KIT, TUM, TAU, UMU, AALTO).

Educating Europe’s Future Engineers for the Next Generation of Mobile Working Machines: ENGAGE will train a new generation of engineers through Industrial Doctorates, equipping them with cutting-edge expertise in AI, robotics, and mechanical engineering. Together, we’re building the future of smart, sustainable mobile machinery.

The project aims to develop advanced methods for evaluating terrain accessibility and drivability using 3D digital environment maps derived from available sensor data. This may involve a combination of geometric and texture-based information, such as semantic segmentation, to create a detailed understanding of the environment. A key objective is to assess the severity of surface deformations in relation to the off-road capabilities of a given machine. This assessment will serve as a foundation for informed decision-making in complex construction or agricultural tasks. Building on this, the project will also focus on the optimal planning of corrective measures that minimize disruption to the primary work process, ensuring efficiency and continuity. As part of the training component, the doctoral candidate (DC) will acquire broad interdisciplinary expertise at the intersection of machine learning, robotics, simulation, and construction processes.

In addition, the DC will contribute to the dissemination of project outcomes through digital and social media channels, including the project website, LinkedIn groups, YouTube video channels, and blog contributions. The project offers the opportunity to pursue a doctoral thesis.

The Supervisory Team will be Marcus Geimer (KIT) and Manuel Bös (Liebherr).

This research center is part of the Helmholtz Association of German Research Centers. With more than 42,000 employees and an annual budget of over € 5 billion, the Helmholtz Association is Germany's largest scientific organisation.