Your work will address how intelligent agents can support and partially automate complex engineering workflows by learning to make structured decisions in environments shaped by constraints, specifications, system models, and long-horizon objectives. 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. Your contributions will help shape Bosch's long-term capabilities in intelligent engineering support systems and agent-based automation for complex technical domains. + strong interest in applying AI to systems engineering tasks such as design-space exploration, requirement analysis, ...
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