[Gkchpa]

Dear all,

After my master's, I was looking for CFD related career, focusing on Aeroacoustics, but I couldn't find something interesting in this area. But I found an interesting Ph.D. topic which is the combination of CFD and thermal simulations and ML is used to optimize the process of crystal growth for semiconductors. But after 4 months, Now I almost got an offer from One of the world-reputed universities to make a Ph.D. in my Interested topic numerical Aeroacoustics of Flyingvehicles.

I am much confused now, I found it hard to find a Job in Aeroacoustics after my master which makes me rethink about choosing it now though I love it, On the other hand, I see ML may take over the next decade in opportunities even in Engineering and research, eventually, I started liking ML for CFD.

I am unable to consider the parameters to make a decision.

Expressing suggestions or Opinions is much appreciated.

[JBeilke]

Sit down and meditate about it.

Why not using ML in the field of aeroacoustics? Usually people do their PhD in one topic but do something completely diffent later.

[sbaffini]

We can't really predict the future but, in general, there is nothing that prohibits you to get a Ph.D. in A while getting a similar competence in B. That is, or should be, quite the point of the Ph.D. in general (within reasonable bounds, of course), and even pretending to be so rigidly in A instead of B is, in my opinion, a wrong depiction of the matter.

For example, what if, during your research, you find out that, say, there is a specific quantum mechanical effect playing a role in a acoustics? Are you simply dropping that route because it is out of your yard?

What I'm sure about, however, yet I know it might sound controversial, is that choosing the Ph.D. as a function of future job opportunities is the most anti-academic, anti-knowledge, counter-productive choice one could make. Also, a complete waste of time, as you will think about money and time during all of it.

Also, ML seems just a piece of the second Ph.D. opportunity, which has CFD, optimization and crystal growth for semiconductors. It seems very likely (yet not sure) that your degree of involvement with ML will be at the level of just using some tool already available out there. Which, honestly, seems nothing that you couldn't do by yourself in anycase as side project while doing aeroacoustics. There will probably be several of such side projects, collaborations, throwing darts at thousands directions, during your Ph.D., that's how it works (or should).

Moreover, for someone, the reputed university might be a factor to consider.

However, in the end, you should also be concrete. Do you really have both offers on the table? If they aren't, maybe do not compromise the only one offer of the two that you actually have.