Job prospects in scientific computing

Click For Summary

Discussion Overview

The discussion revolves around job prospects in the fields of computational physics and computational biology, focusing on employability in both industry and research-oriented positions. Participants explore the implications of choosing a specific sub-field and the skills necessary for securing employment.

Discussion Character

  • Debate/contested
  • Exploratory
  • Technical explanation

Main Points Raised

  • Some participants suggest that job prospects may depend more on the specific skills developed rather than the chosen sub-field itself.
  • There is a belief that regardless of the field chosen, academic positions are rare and that many may eventually leave academia.
  • One participant expresses concern about the risks of pursuing a degree without clear employment statistics for the specific field.
  • Another participant emphasizes the importance of being the best candidate and actively seeking job opportunities, regardless of statistical job availability.
  • Some participants mention that programming skills, data handling, and mathematical modeling are highly marketable and beneficial for long-term employment.
  • There is a discussion about the feasibility of obtaining jobs in specific sub-fields such as electromagnetism, geophysics, neurosciences, biophysics, and bioinformatics.
  • One participant expresses a desire to avoid corporate jobs unrelated to science, while another clarifies that they would be open to corporate roles that align with their field of study.
  • Specific companies like ANSYS and COMSOL are mentioned as potential employers in relevant industries.

Areas of Agreement / Disagreement

Participants do not reach a consensus on the best sub-field for job prospects, and multiple competing views remain regarding the balance between personal interest and employment opportunities.

Contextual Notes

Participants express varying degrees of uncertainty about job availability in their chosen fields and the implications of pursuing a degree in computational science. The discussion highlights the importance of individual skills and flexibility in job search.

Who May Find This Useful

Individuals considering a degree in scientific computing, particularly in computational physics or computational biology, as well as those interested in job prospects in these fields.

quantknight
Messages
44
Reaction score
3
Which sub field of scientific computing has better employ ability and job prospects? (within computational physics & computational biology). I meant both in industry and research oriented jobs where we would use the skills and knowledge relevant to the degree.
 
Physics news on Phys.org
I certainly do not know the answer to your question, but I would observe that, to a large extent, we make our own opportunities. Do which ever one excites you the most, be good at it, and the work will come.
 
  • Like
Likes   Reactions: quantknight
Dr.D said:
I certainly do not know the answer to your question, but I would observe that, to a large extent, we make our own opportunities. Do which ever one excites you the most, be good at it, and the work will come.

Even I would like to do the one which I am interested in, isn't it too risky to do without knowing what are the employment status for the particular degree??
 
You are not employed by the statistics, but rather by a single, specific employer. Even if there is only one job available in the entire universe, if you get it, that should be good enough. To get that one job, you probably have to be (1) the best candidate, and (2) aggressive in seeking the job.
 
It's difficult to say because both fields are fairly broad, and I think a lot will come down to the specific skills that you develop rather than the specific sub-field you work in. Computational problems tend to change rather quickly. The big problems right now are not likely to be the same a decade from now.

It's probably safe to assume that regardless of which field you choose you won't end up in academia. That's not to say an academic position is impossible, just that they're hard to come by these days - statistically speaking. So you're much more likely to end up eventually leaving academia. From that perspective, programming skills, programming language fluency, learning how to work with large data sets, parallel processing techniques, mathematical modelling, learning how to properly document code, etc. are going to be highly marketable skills that will help you to transition out of academia and keep you employed in the long term.
 
Dr.D said:
You are not employed by the statistics, but rather by a single, specific employer. Even if there is only one job available in the entire universe, if you get it, that should be good enough. To get that one job, you probably have to be (1) the best candidate, and (2) aggressive in seeking the job.

I agree with your point, but practically speaking, I have commitments like debts to repaid after graduating, so I would choose the one which balances both my interest and better employment opportunities.
 
Choppy said:
It's difficult to say because both fields are fairly broad, and I think a lot will come down to the specific skills that you develop rather than the specific sub-field you work in.

Thank you. Since you mentioned both are broad branches, I have narrowed down my interests into the following sub fields, computational physics - electromagnetism & geophysics, computational biology - neurosciences, biophysics, and bioinformatics. I will pursue the one whichever is feasible to me. So is it possible to get a job in industry or research in these sub fields?

Choppy said:
It's probably safe to assume that regardless of which field you choose you won't end up in academia. That's not to say an academic position is impossible, just that they're hard to come by these days - statistically speaking. So you're much more likely to end up eventually leaving academia. From that perspective, programming skills, programming language fluency, learning how to work with large data sets, parallel processing techniques, mathematical modelling, learning how to properly document code, etc. are going to be highly marketable skills that will help you to transition out of academia and keep you employed in the long term.

Frankly speaking, I have already worked in a corporate company, and I don't want to end up in a corporate job again just for the programming skills . I am pretty much interested in science and that's the reason I want to pursue the master's degree. I would like to work in the job where I would use the skills at least relevant to the science field (not some banking or software product). If there are no jobs available, I would pursue research on the topics (teaching is also okay for me). So would it be a mistake to to join a computational science degree and don't want to end up in a corporate job irrelevant to the science field?
 
quantknight said:
Thank you. Since you mentioned both are broad branches, I have narrowed down my interests into the following sub fields, computational physics - electromagnetism & geophysics, computational biology - neurosciences, biophysics, and bioinformatics. I will pursue the one whichever is feasible to me. So is it possible to get a job in industry or research in these sub fields?

The short answer is yes, it is possible to get a job in industry or research in the subfields you mentioned. One of my good friends who has a PhD in applied math is working in bioinformatics (but I'm sure a masters may suffice as well). Of course, much will depend on how flexible you are in terms of what type of industry job you are looking for, and how flexible you are in terms of relocating to where the jobs are (certain industrial or research jobs in, say, bioinformatics, are highly clustered in specific locations e.g. near San Francisco, Boston, etc.)

Ditto for areas like computational applications in geophysics.

Frankly speaking, I have already worked in a corporate company, and I don't want to end up in a corporate job again just for the programming skills . I am pretty much interested in science and that's the reason I want to pursue the master's degree. I would like to work in the job where I would use the skills at least relevant to the science field (not some banking or software product). If there are no jobs available, I would pursue research on the topics (teaching is also okay for me). So would it be a mistake to to join a computational science degree and don't want to end up in a corporate job irrelevant to the science field?

I suppose you need to clarify what you mean by a "corporate job". Would you be fine working, say, for a software company specializing in, say, tools for bioinformatics/genomic analysis? Or a company specializing in developing remote sensing software for geophysics?
 
StatGuy2000 said:
I suppose you need to clarify what you mean by a "corporate job". Would you be fine working, say, for a software company specializing in, say, tools for bioinformatics/genomic analysis? Or a company specializing in developing remote sensing software for geophysics?

Thank you. As long as I work related to the field I studied, I am fine with this corporate job then. What I meant was that I have no interest in the domains of software products, banking products, kind of jobs. May I know what is the name of the particular industry? or few company names would suffice.
 
  • #10
quantknight said:
Thank you. As long as I work related to the field I studied, I am fine with this corporate job then. What I meant was that I have no interest in the domains of software products, banking products, kind of jobs. May I know what is the name of the particular industry? or few company names would suffice.

ANSYS
COMSOL
 
  • #11
clope023 said:
ANSYS
COMSOL
Thank you.
 

Similar threads

  • · Replies 3 ·
Replies
3
Views
5K
  • · Replies 9 ·
Replies
9
Views
4K
  • · Replies 8 ·
Replies
8
Views
3K
  • · Replies 7 ·
Replies
7
Views
4K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 11 ·
Replies
11
Views
7K
  • · Replies 13 ·
Replies
13
Views
3K
  • · Replies 5 ·
Replies
5
Views
2K