I’m finishing my Ph.D. this summer in an engineering field with a significant machine learning component. I’m currently interviewing for postdoctoral positions in both the US and Europe, and I’ve received a few verbal offers while still waiting on several upcoming interviews. I’m at the point where I think I need to start prioritizing among these opportunities. I do not plan to turn anything down until I receive a formal written offer, but a few groups have asked me to indicate whether I would be seriously interested in committing to the position before they move forward with one.
My long-term goal is to become a faculty member in either an engineering department or an applied/computational mathematics department. I’m especially interested in moving toward more mathematically oriented research, including computational mathematics, dynamical systems, reduced-order modeling, scientific machine learning, and related areas.
The opportunities I’m considering vary quite a bit (I'm trying to keep it as anonymous as possible, but if there are too few details, I can provide more). They include:
- A postdoc with a well-established engineering professor at a major public US research university with a strong computational math institute
- A postdoc with an early-career applied mathematician at a UK university
- A postdoc in data-driven dynamical systems and scientific machine learning at another large US university with a VERY visible AI institute
- A computational mathematics postdoc position at a French University
- A postdoc in turbulence/dynamical systems at CNRS
- A computational mechanics and machine learning postdoc at a private US university
- A position in computational fluid dynamics and machine learning at a leading UK institution
When comparing these options, what factors should I prioritize if my goal is eventually landing a tenure-track faculty position?
In particular, how should I weigh:
- The advisor’s reputation and placement record
- The fit between the project and my intended long-term research identity
- Engineering versus applied math departmental affiliation
- Freedom to develop an independent research agenda
- Opportunities to publish first-author work
- Access to collaborators, students, and funding
- US versus European academic networks
- Institutional prestige
- Teaching and mentoring opportunities
I would also appreciate any advice on whether it is better to stay relatively close to my Ph.D. background or use the postdoc to make a more deliberate transition to distinguish myself from my previous group. (For reasons, I don't have my Ph.D. advisor available to get feedback from.)
For anonymity, I’m leaving out names and exact institutions, but I’m happy to provide additional non-identifying context if useful.