What fields have the most postdoc positions?

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The discussion centers on the increasing demand for strong computational skills in postdoctoral applications, particularly for those transitioning from experimental physics to applied mathematics. The individual, having pursued a master's in applied math after a PhD in experimental physics, expresses concerns about the relevance of their new skills to their postdoc prospects. Key insights include the importance of publishing extensively and networking through conferences to enhance competitiveness. However, it is noted that postdoc positions often require specific skill sets closely aligned with the research area, making it challenging for those with unrelated backgrounds to compete. While expanding computational skills is generally viewed positively, the relevance of a master's in applied math to securing a postdoc in thin films or similar fields is questioned, suggesting that unless one plans to shift focus to theoretical problems, the master's may not significantly enhance postdoc opportunities.
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These days it seems like everywhere you apply one of the requirements is having "strong" and sometimes "extensive" "computational skills".

Well I already started a masters in applied math (after my PhD in experimental physics = zero computational skills). Before starting the masters it seemed like I was simply wasting time year after year and distancing myself away from research (being a part time instructor making less money than a graduate student with no promising future year after year :[)

I learned few lessons from this:
1. publish publish publish and publish even more!
2. make as many connections as possible and go to every conference you can!

My question is: will a masters in applied mathematics (in modeling and computing) help in the postdoc application (of course in addition to publishing and having connections)? Any suggestions on what I should do while in the masters program to enhance my prospects?

I appreciate any input.
 
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This really depends on the individual post doc positions that you're applying for. In my experience, post-doctoral positions are generally set up for people with very specific skill sets. That means they already have experience working on a particular problem or set of problems. So simply having some programming or computer skills in combination with an unrelated background is not going to be competative against individuals who essentially have already done a PhD in that area.

It's necessarily a bad idea to expand your skill set though.
 
What was your PhD research in?
 
Thank you Choppy, your suggestions are always helpful. When I applied to postdoc positions a while back, I found that most of them always require "excellent" "extensive" computational skills along side with the area of research they want you for.

Choppy said:
It's necessarily a bad idea to expand your skill set though.

I assume you wanted to say "It's not necessarily ..."?
 
Physics_UG said:
What was your PhD research in?

Solid state physics, "thin films" etc.
 
Was your PhD experimental?
Why would you need "computational skills" for a post-doc related to thin films?
Are you sure this wasn't just words added by HR departments?
Presumably you are already familiar with the software relevant to your fields if you've done a PhD (perhaps software for AFM analysis etc) and that should be all you need.

A masters in math might be a good idea for other reasons, but I can't see why it would help you get a post-doc related to your PhD research; unless you are planning to swtich fields and work on some theoretical "technical" problem as a post-doc (somethign akin to writing image analysis software for thin films characherisation). However, that would be VERY specilized and your chances of finding such a position would presumably be slim.
 
sabq said:
Thank you Choppy, your suggestions are always helpful. When I applied to postdoc positions a while back, I found that most of them always require "excellent" "extensive" computational skills along side with the area of research they want you for.



I assume you wanted to say "It's not necessarily ..."?

Oops. Yes.
 

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