Work environment

Volkswagen Group Innovation drives the development of future mobility concepts and advanced technologies for all brands of the Volkswagen Group worldwide. With the innovation centers in Europe, Asia, and the United States, we leverage local expertise to develop solutions with both global and regional relevance. Working in an interdisciplinary environment, you will explore cutting-edge technologies, apply modern development methods in the automotive domain, and translate research insights into practical vehicle applications. As part of your PhD, you will work on context orchestration and engineering for next-generation intelligent vehicles. Your research will focus on understanding and structuring dynamic context information within and beyond the vehicle, spanning perception, cognition, and action. A key challenge will be investigating how heterogeneous context sources can be efficiently orchestrated across constrained in-vehicle hardware and extended cloud environments. We are looking for a proactive personality with an interest in computational linguistics, intelligent systems, and agentic AI, who contributes to an interdisciplinary team and actively shapes the mobility of tomorrow. The primary place of work is our center in Wolfsburg. We are looking forward receiving your application!

Possible Tasks within this Role

• Develop, analyze and evaluate context‑driven AI components and hybrid agentic systems across perception, cognition, and action
• Investigate methods for context acquisition, fusion, and orchestration, including interior/exterior camera data, sensor streams, navigation data, vehicle settings, and internet-based information
• Research and design architectural concepts for context-oriented AI systems on vehicle SoCs and cloud integration, including requirements engineering, model fine-tuning, and hardware-aware optimization
• Analyze quantitative and qualitative approaches for evaluating system performance under real‑world conditions
• Work with AI‑agent frameworks for training, designing and optimizing context‑aware intelligent workflows

The final doctoral topic is defined together with the professor. The prerequisite for the cooperation is the confirmation of supervision as well as a confirmed delimitation of topics by the professor of a university or research institution entitled to confer a doctorate.

Qualification requirements

• Good to very good university degree qualifying for doctoral studies in computer science, data science, electrical engineering or a related field
• Advanced proficiency in coding, including experience with data processing, optimization techniques, and software engineering best practices
• Deep understanding of AI/ML concepts, including generative models, agentic architectures, and multi‑modal systems
• Experience with applied AI research, such as model training/fine‑tuning, benchmarking, or developing experimental prototypes
• Strong analytical and problem‑solving abilities, ideally demonstrated through prior thesis work, publications, or research projects
• German language level A2 and English language level C1

Keywords

Context Fusion, Intelligent Vehicle Systems, In‑Vehicle SoC Optimization, Hybrid Cloud‑Vehicle Architectures, AI‑Defined Vehicle