PhD in Safety Contracts for Physical AI

About the role

The design and development of innovative safety contracts will be your core focus, establishing formal runtime interfaces to ensure safe interaction between decision‑making and control in autonomous systems. You will translate research findings into concrete applications, especially in vehicle motion control and autonomous driving.

Key responsibilities

• Define assumptions, guarantees, and adaptation rules for modular autonomy stacks across different abstraction levels.
• Apply optimal control, sequential decision‑making under uncertainty, and reinforcement learning to create robust, high‑performance solutions.
• Derive feasibility margins, uncertainties, and safety contracts from real‑world data using machine learning.
• Contribute to modular, safety‑by‑construction learning‑enabled autonomy and enable runtime verification.

Required profile

• Excellent master’s degree in Control Engineering, Robotics, Computer Science or a related field.
• Solid background in optimization or control and programming proficiency in Python.
• Enthusiastic about technical challenges, able to work in interdisciplinary teams and take initiative.
• Very good English; German is an advantage.

Required skills

• Python programming
• Optimization and control theory
• Machine learning and reinforcement learning