Doktorand*in für Promotion "Autonomous Reality Capture for AI-native Digital Factory Twins"

Tasks

The dissertation is based in the MO360 Digital Factory Twin department at Mercedes-Benz Manufacturing Engineering. The team drives the digital transformation of production planning and factory development by building the Digital Factory Twin as a central platform for planning, analyzing and optimizing future production systems.

The research focuses on autonomous reality-capture systems and self-updating digital twins for factories. You will investigate approaches at the intersection of robotics, computer vision and generative AI, in close cooperation with Mercedes-Benz Research and Development India and within current ARENA2036 research activities.

Possible research questions

• How can autonomous drones and mobile robots safely and efficiently capture production environments?
• How can image, video, LiDAR and sensor data be automatically combined into consistent digital twins?
• What potential do Vision Language Models and multimodal foundation models offer for understanding industrial environments?
• How can changes in factories be automatically detected, classified and documented?
• Which methods enable reality-capture data to be transferred directly into semantically enriched 3D models?
• How can safety, privacy and governance requirements for autonomous data-capture systems be addressed?
• How can autonomous capture systems be integrated into industrial digital-twin and metaverse platforms?

Expected scientific contribution

• Evaluation and prototypical implementation of autonomous reality-capture methods in real Mercedes-Benz factory environments
• Combination of robotics, computer vision and generative AI for automated capture and interpretation of production areas
• Scientific insights for self-updating digital twins
• Concrete benefits for planning, operation and optimization of future production systems

The final research topic will be defined in close coordination between you, the university and Mercedes-Benz. The position can begin in mid-October 2026. Supervision of the doctoral project by a university professor is required.

Qualifications

• Above-average master's degree in computer science, robotics, electrical engineering, computer engineering, mechatronics, data science, computational engineering or a comparable subject
• Very good Python skills
• Initial experience with machine-learning frameworks such as PyTorch or TensorFlow
• Initial practical experience with generative AI models, Vision Language Models or multimodal foundation models
• Interest in autonomous systems, computer vision, robotics and digital twins
• Very good written and spoken English
• Ability to abstract complex technical questions scientifically, with strong analytical and conceptual thinking
• Independent, structured working style and enjoyment of interdisciplinary collaboration

Desirable knowledge includes digital twins, reality-capture technologies, LiDAR and sensor-data processing, SLAM, Gaussian Splatting, neural rendering, 3D reconstruction, deep learning, autonomous navigation and NVIDIA Omniverse.

Additional information

Doctoral candidates benefit from Mercedes-Benz expertise, an international network, research materials, insights into the company and personal mentoring in addition to their university. Please submit an online application with a CV, cover letter and certificates.

Applicants with severe disabilities or equivalent status are welcome. For application-process questions, HR Services can be reached at myhrservice@mercedes-benz.com or 0711/17-99000.