Considering a PhD at the intersection of AI and Systems Engineering
Hello Reddit, I’m currently exploring the possibility of pursuing a PhD in North America, Europe, or elsewhere, and I’d really value some perspectives from people working in Systems Engineering, MBSE, AI, or adjacent research areas.
My background is somewhat unconventional for SE. I completed my bachelor’s in Electrical & Electronic Engineering, then moved into Computer Science with a focus on AI for my master’s. Since then, I’ve spent the past few years working professionally in AI, Natural Language Processing, Automatic Speech Recognition and Engineering/Software with my current work being closely related to Systems Engineering and MBSE. This exposure to the SE/MBSE space has gradually made me interested in making it a potential long-term specialization.
What particularly interests me is the intersection of AI × Systems Engineering × MBSE — for example, using AI to assist with requirements, system architecture, modeling, traceability, verification/validation, and other parts of the systems lifecycle.
At this point, I’m considering whether a PhD would be the right next step and would appreciate some honest perspectives from people who have been in the field for a while.
A few things I’m particularly curious about:
How valuable is a PhD for building a long-term career in Systems Engineering/MBSE research and practice?
Would an interdisciplinary profile combining engineering + AI + MBSE, along with some practical exposure to the SE/MBSE industry, be useful for Systems Engineering research groups?
Which areas at the AI–SE/MBSE intersection have genuine research potential beyond simply applying LLMs to existing workflows?
Would you recommend a PhD specifically in Systems Engineering, or pursuing one through Computer Science, Electrical Engineering, Aerospace, etc. with a Systems Engineering/MBSE-focused research topic?
How important are SysML/SysML v2, requirements engineering, system architecture, formal methods, and MBSE fundamentals for someone coming from an AI background? I know the basics of SysML and SysML v2 and am still learning and practicing them.
More importantly, how do experienced systems engineers view the long-term resilience and career prospects of SE/MBSE as engineering workflows become increasingly AI-enabled? Which parts of systems engineering are likely to become more valuable, and which parts may become increasingly automated?
For those already in academia or industry, what would you consider a strong profile for someone with an AI/engineering background trying to deepen their involvement in Systems Engineering?
I’d also be interested in hearing from professors or research groups working on AI-assisted systems engineering, intelligent MBSE, AI for engineering design, or related topics. If you’re working in this area, I’d be genuinely interested in learning about your research.
I’m still at the exploration stage regarding the PhD itself, but I already have some practical exposure to the SE/MBSE ecosystem. I’m particularly interested in perspectives based on actual experience rather than generic career advice.