Postdoctoral Researcher in AI-Driven Methods for Cyber-Physical Systems

Job summary

A postdoctoral position is available focused on AI-driven methods and tools for model-based systems engineering of distributed cyber-physical real-time systems. The role is part of a project aimed at enhancing software-defined vehicle engineering automation through AI-assisted techniques.

Qualifications

• PhD degree (or equivalent) in a relevant field.
• Research experience in cyber-physical systems or real-time computing combined with machine learning.
• Familiarity with real-time systems, embedded or distributed systems, model-based engineering, formal methods, optimization, networking, or Time-Sensitive Networking (TSN).
• Proficient programming skills and experience with research prototypes.
• Proven track record of research publications and collaboration with peers.

Responsibilities

• Develop AI-driven methods and prototype tools for analysis and configuration in model-based engineering workflows.
• Implement AI-based methods to predict or approximate analysis results, verifying them with deterministic tools.
• Utilize AI-assisted combinatorial optimization for various engineering challenges.
• Synthesize models, constraints, test cases, and prototype code using large language models.
• Conduct experiments on distributed architectures inspired by vehicle systems.
• Publish research findings and collaborate with project partners.
• Supervise students and engage in teaching and proposal work as needed.

Skills

• Strong analytical and problem-solving skills in the context of distributed systems.
• Ability to work collaboratively in a multidisciplinary environment.

Education

• A PhD degree (or equivalent) is required for this position.

Tools

• Experience with programming languages and tools relevant to AI, machine learning, and systems engineering.