PhD - Safety Contracts for Physical AI
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Job Description
• 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 precisely define assumptions, guarantees, and adaptation rules for modular autonomy stacks to secure system integrity across different abstraction levels.
• More over, you will utilize advanced methods of optimal control, sequential decision-making under uncertainty, and reinforcement learning to develop robust, high-performance solutions.
• Using machine learning, you will derive feasibility margins, uncertainties, and the safety contracts themselves from real-world data.
• Translating research findings into concrete applications is a key goal, particularly in the domain of vehicle motion control and autonomous driving, to safely bridge the gap between high-level decisions and physical reality.
• Last but not least, you will contribute significantly to making learning-enabled autonomy modular by design, guaranteeing safety by construction, and enabling verification at runtime.
Requirements
Function: Research
Experience Level: Entry Level