Computational Physics Concentration

In summary: If you want to know more about computational biophysics - google it and see what you find. If you want to know more about computational optoelectronics - google it and see what you find. The internet is a wonderful place!
  • #1
CupOfNoodles
2
0
Hello, I'm new to the Physics Forums website. I am in my 5th (and last) year of undergraduate Electrical Engineering, and am planning on applying for a PhD in some computational field. I'm not sure, however, what specific field I want to go into, and I was hoping someone could give me some suggestions. Here is a layout of what I am thinking and why...

How do I know I want to do computational research?
I have been working with a business doing experimental material science research for a little over a year. I really enjoy the research process, but I have found that I can tolerate a full days worth of coding more than a full days worth of lab work. I often keep a few hands-on projects at home to work on in my free time, which is why I thought I originally wanted to do lab work, but I think I would rather keep the tinkering as a hobby.

Of course, it goes without saying, I really have a passion for numerical work. I have had classes in Numerical Analysis, Data Analytics, Math Modelling etc... and I enjoy those courses the most. I can't get enough of this stuff.

What am I looking for in my research?
I want to apply current numerical techniques to create simulations to answer science questions (the subject is where I need help deciding). I want to analyze experimental data to help build better models and more accurate simulations. I hope to find a science that will call for collaboration with experimentalists, uses skills that easily translate to similar work in industry, and allows me to be versatile in my research (no pigeonhole). I hope this makes sense

What are my favorite courses/topics so far?
In no particular order...
Numerical Analysis, Linear Algebra, GPS Design, E&M, Probability and Statistics, Radio Wave Propagation, Control Systems.

My first thought was to look at plasma physics, since I enjoyed a lot of courses that serve as a foundation for it. Unfortunately, my school does not offer a plasma physics course for undergraduates, but I have studied it a little, and recently started working through a textbook. Part of me is also interested in biology/medical related research, but I have very little background knowledge of this field. My interest comes from very frequent conversations with a close friend that has a Biology degree.

Let me know if I can add anything, or if something isn't clear. Thank you!
 
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  • #2
All I can do is suggest questions you can ask yourself. I can't make this kind of decision for you.

When you have studied different topics, and done different tasks related to these topics, when have you been happiest? When have you been the most focussed and deeply involved in your work? When have you felt the most satisfaction with being involved in the task and in completing the task? Which subjects, and tasks within those subjects, do you find yourself returning to eagerly? Which ones would you be sad to stop working on?

Of all the subjects and tasks you have worked on, which ones are you really good at? Which ones do you finish with completeness, accuracy, and efficiency? Which ones do you have the most depth in? Which ones do you make the fewest mistakes in?

If you sit and contemplate doing a task for the next month, year, several years, which ones do you feel good about?

If there are still lots of possible choices (happy for you :smile:) then you should think about more mundane things. Which one will make you more money? Which one will have a better chance of getting you a job? Which one will be more available at a university you want to attend? Which one has the higher reputation university or professor?
 
  • #3
You can look into computational electromagnetics/optics which is the field I currently work in. It fits really well with some of the interests you have listed and there are a large variety of projects! The research is commonly done in departments of electrical engineering, mathematics, optics, and physics. You can try just googling and looking for research groups and read their summaries as well as some papers - this is true of all fields. So if you want to know more about computational plasma physics - google it and see what you find.
 

1. What is Computational Physics Concentration?

Computational Physics Concentration is a specialized field of study that combines the principles of physics and computer science to solve complex problems in physics using computational methods. It involves the use of numerical simulations, mathematical models, and algorithms to analyze physical systems and phenomena.

2. What are the key skills required for a Computational Physics Concentration?

Some key skills required for a Computational Physics Concentration include proficiency in programming languages such as Python, C++, and Fortran, knowledge of numerical methods and algorithms, understanding of physics principles and theories, and critical thinking and problem-solving abilities.

3. What are the career opportunities for someone with a Computational Physics Concentration?

Graduates with a Computational Physics Concentration can pursue careers in a variety of fields, including research and development, data analysis, software engineering, and scientific computing. They can also work in industries such as aerospace, energy, and defense.

4. Is a strong background in physics necessary for a Computational Physics Concentration?

Yes, a strong foundation in physics is essential for a Computational Physics Concentration. Students should have a good understanding of classical mechanics, electromagnetism, quantum mechanics, and other fundamental physics concepts to apply them in computational simulations and models.

5. What are some examples of real-world applications of Computational Physics Concentration?

Computational Physics Concentration has a wide range of applications, including weather forecasting, climate modeling, materials science, astrophysics, and biophysics. It is also used in developing new technologies, designing advanced materials, and understanding complex systems in nature, such as the human brain.

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