You will investigate how reinforcement learning, hierarchical decision-making, model-based methods, and planning can be combined with modern agentic AI architectures to support engineering tasks such as architecture exploration, requirement analysis, system-level trade-off evaluation, validation support, and process optimization. * This role centers on the design of AI agents that do not merely respond to prompts, but can interact with engineering artifacts, reason over goals and constraints, and improve their behavior through feedback, simulation, and optimization. + strong interest in applying AI to systems engineering tasks such as design-space exploration, requirement analysis, architecture optimization, verification support, or engineering workflow automation + ability to formulate engineering problems as sequential decision-making or optimization tasks
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