How to decide between 2 fields of research(Astrophysics vs Brain Modelling)?

In summary, Jack is undecided about whether to pursue a research project in computer science or mathematics. He is passionate about both subjects, however, and is unsure which field would be better for him. He would like to focus on one project, but is indecisive about which one to choose. He has been told that you should only focus on one area of research, but Jack is interested in both fields and does not want to choose one over the other. He is open to studying computability theory, however, and thinks it would be helpful in any research project he pursues.
  • #1
neurocomp2003
1,366
3
Hi,
I get my grad school decision in about 2 weeks.:cry:
I'm having a problem deciding between 2 fields that I would love to do a research project in. Both involve Computational/Simulations Science [Computer Science(computability and 3D engine development) & Mathematics].

The 1st is ALife/Brain Modelling/Adaptive Learning(Neural Networks,Evolutionary Techniques).
The 2nd is Astrophysics/Planetary/Geophysics(multiscale science)

The question I have is how would you choose between the two? What questions would you ask if you were in my place?

I am passionate about both and began studying them at the undergrad level before I got lost. And i can see myself in either field. I have been told that you should only focus on one project which has led to this indecision.
Also is a student allowed to pursue 2 Phd's(1 after the other)? Is there any point?

Thank you for helping me, in advance
Jack
 
Physics news on Phys.org
  • #2
I'd choose the neural network path, but that's just my personal preference. There are some great potential advances in the NN field, IMO. In your other choice, would you be focusing on practical things like Earth weather modelling and earthquake modelling, etc.? Or would you be wanting to focus more on the astrophysics aspect?
 
  • #3
hi berkeman thanks for replying. I was thinking of designing code to handle both aspects actually. My main interest is creating generic code for N-body simulations of various levels of science but the project itself would be focused on any of those mentioned above(i guess it would depend on the consulting supervisor).

So you think there's greater potential in NNs and Adaptive Learning. I will have to take that into great consideration.
Thank you again.
 
  • #4
What hardware are you targeting to run you code on? Will it rely on massive parallelism? For the kind of simulations that you are talking about, it would seem like a good idea early on to decide what physical platforms are best, and use that to help you plan your code architecture.
 
  • #5
berkeman: I'm hoping to start off with one computer...for simplicity(still learning about Nbody)... but once I'm in the 2nd year(depending on how it is taught in grad school) i'd like to go into high computing/parallelism.
Do you know of any references(books/websites) i can take alook at to understand the difference in coding architecture that you mentioned above(going from a single PC to a supercomputer)
 
Last edited:
  • #7
My choice would be neural networks, but that may be because I recently read Complexity, by Waldrop. :smile: I would second what berkeman had to say about this field, though.
 
  • #8
I officially got accepted so does anyone else have advice? I got till sept to decide i think.
 
  • #9
neurocomp2003 said:
Hi,
I get my grad school decision in about 2 weeks.:cry:
I'm having a problem deciding between 2 fields that I would love to do a research project in. Both involve Computational/Simulations Science [Computer Science(computability and 3D engine development) & Mathematics].

The 1st is ALife/Brain Modelling/Adaptive Learning(Neural Networks,Evolutionary Techniques).
The 2nd is Astrophysics/Planetary/Geophysics(multiscale science)
Neither of those involves computability theory. You mean algorithms and numerical techniques?

Personally I would also prefer neural networks and AI. The industrial age automated and made reproducible the work of manual labor--the computer age will automate and make reproducible the work of thought.
 
Last edited:
  • #10
computability theory isn't used directly in them but its about studying what's possible and what's not(or what's efficient and what's not), algorithms and numerical techniques IMO is part of the foundations of 3D-engine development.
 
Last edited:
  • #11
Computability theory is just about what's possible or what's not, not about efficiency. Pretty much anything you'd be doing in those fields is going to be possible. I think computability is applied more in fields like compiler design, where it helps to know that no matter what you do you can't write a perfect tool to detect unreachable code.
 
Last edited:

1. What are the main differences between astrophysics and brain modelling?

Astrophysics is the study of the physical properties and behavior of celestial objects such as stars, planets, galaxies, and the universe as a whole. Brain modelling, on the other hand, is the study of the structure and function of the brain, including how it processes information and controls behavior.

2. How do I know which field is a better fit for me?

The best way to determine which field is a better fit for you is to consider your interests, strengths, and career goals. If you are fascinated by outer space and have a strong aptitude for physics and mathematics, astrophysics may be a better fit. If you are more interested in the human brain and have a background in biology or neuroscience, brain modelling may be a better fit.

3. What are the potential career opportunities in each field?

Career opportunities in both astrophysics and brain modelling can vary, but some common options include research positions at universities or government institutions, teaching positions, and work in the private sector such as in pharmaceutical or technology companies.

4. Can I pursue both fields simultaneously?

While it is possible to have a broad range of interests and skills, it may be difficult to fully dedicate yourself to both astrophysics and brain modelling simultaneously. These are complex and diverse fields that require significant time and effort to excel in, so it may be more beneficial to focus on one field while remaining informed and interested in the other.

5. How can I learn more about these fields before making a decision?

There are many resources available to learn more about astrophysics and brain modelling, such as books, articles, podcasts, and online courses. Additionally, reaching out to professionals in each field for informational interviews or job shadowing opportunities can provide valuable insight into the day-to-day work and career opportunities in each field.

Similar threads

Other How much does one's undergraduate field of research matter?
    • STEM Academic Advising
Replies
10
Views
2K
Admissions Opening the door to an Astrophysics PhD after a 5 year gap
    • STEM Academic Advising
Replies
11
Views
634
Courses How should I decide on which research project to take on this year?
    • STEM Academic Advising
Replies
1
Views
913
Other How to become an amateur physicist
    • STEM Academic Advising
Replies
4
Views
2K
Admissions Curious about my grad school prospects
    • STEM Academic Advising
Replies
3
Views
929
Which MSc to do after BSc physics if you love to code?
    • STEM Academic Advising
Replies
10
Views
1K
What topics in a Physics degree don't appear in an Astrophysics degree?
    • STEM Academic Advising
Replies
8
Views
1K
Admissions Critique on research statement
    • STEM Academic Advising
Replies
6
Views
1K
Admissions (international) My chances of getting into top Astrophysics programs?
    • STEM Academic Advising
Replies
13
Views
2K
Programs Applying for Physics REUs: My Journey into Astrophysics
    • STEM Academic Advising
Replies
5
Views
1K

Hot Threads

Recent Insights

Back
Top