High impact on society, reality tested, and heavy use of logic and symbolic math

In summary, the individual is looking for a career shift and is seeking a career that involves heavy use of advanced mathematical concepts, has readily testable theories, and has a significant impact on humanity. They also prefer a field where people are driven by passion and curiosity. They have a background in computer engineering, applied discrete mathematics, and electrical engineering. Suggestions for potential careers include computational physics, working for companies like Wolfram or Comsol, or getting involved in startup companies. However, jobs that are strictly devoted to working with symbolic math or equations may be rare. The individual also expresses a preference for a higher conceptualization to "grinding" ratio in their work.
  • #1
ygolo
30
0
I am looking to make a career shift.

I am looking for a career track with the following characteristics:

1) Heavy use (and need to learn) advanced mathematical concepts (especially symbolic in nature). I want to be working with equations and logic in a symbolic manner on a daily basis.

2) A career in which the theories are readily tested/testable. I may or may not want to do the testing, depending on how tedious it is. If it is tedious to test, I would rather not. If the testing is easy or fun, I like having the immediate feedback.

3) A career where the work will be of great significance to humanity. --The potential for ground breaking discoveries or inventions that move society forward.

Any suggestions?Also, what credentials would I need to obtain to enter these fields?

So far, I have:
A B.S. in Computer Engineering
A B.S. in Applied Discrete Mathematics
An M.S. in Electrical Engineering
8+ years in Integrated Circuits industry
 
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  • #2
After further discussion with others, I've decided to add a fourth criteria:

4) A field in which people are mainly there due to their passion, curiosity, etc.
 
  • #3
If anyone here knew of a job like that, they'd be doing it, and they wouldn't tell you.
 
  • #4
ygolo said:
I am looking to make a career shift.

I am looking for a career track with the following characteristics:

1) Heavy use (and need to learn) advanced mathematical concepts (especially symbolic in nature). I want to be working with equations and logic in a symbolic manner on a daily basis.

2) A career in which the theories are readily tested/testable. I may or may not want to do the testing, depending on how tedious it is. If it is tedious to test, I would rather not. If the testing is easy or fun, I like having the immediate feedback.

3) A career where the work will be of great significance to humanity. --The potential for ground breaking discoveries or inventions that move society forward.

4) A field in which people are mainly there due to their passion, curiosity, etc.

Any suggestions?


Also, what credentials would I need to obtain to enter these fields?

So far, I have:
A B.S. in Computer Engineering
A B.S. in Applied Discrete Mathematics
An M.S. in Electrical Engineering
8+ years in Integrated Circuits industry

Probably computational physics. Companies like Wolfram or Comsol, which develop simulation/engineering software.

People who get involved in startup companies have the passion, curiosity, etc.
 
  • #5
Astronuc said:
Probably computational physics. Companies like Wolfram or Comsol, which develop simulation/engineering software.

Only if he equates computer simulations with "working with equations and logic." That might seem a reasonable connection to us, but a lot of people out there would imagine "working with equaitons and logic" to require us to actually push the equations around, not use a computer to solve second order diffeq.

I'm actually going to guess that what he wants doesn't really exist anymore, though I could be underestimating how well he understands the subject.
 
  • #6
I think jobs that are strictly devoted to symbolic math or equations are few and far between.

In my job, we do simulations which are basically finite element analyses of the thermo-mechancial behavior of solid objects. We use proprietary software developed in-house as well as commercial software like ANSYS, ABAQUS, Fluent, . . .

Part of the development process is to sit down with pencil/pen and paper and derive the consitutive equations, and then cast them into computer code. Then there are an array of thermophysical and mechanical properties models. The theory manual is extensive.

Every now and then we get new data with which to modify an existing model or add a new model. That involves fitting experimental data, or manipulating differential or differentio-integral equations, and casting them into code (FORTRAN).

Our simulations are validated against experiments, and in some cases are used to make predictions, which are ultimately tested by performance or in some cases measurements.

Part of the time we develop methods, but a lot of the time, we apply the methods.

And my colleagues and I are pretty passionate about what we do, and we like to think that it benefits humanity in someway.
 
  • #7
Locrian said:
Only if he equates computer simulations with "working with equations and logic." That might seem a reasonable connection to us, but a lot of people out there would imagine "working with equaitons and logic" to require us to actually push the equations around, not use a computer to solve second order diffeq.

I'm actually going to guess that what he wants doesn't really exist anymore, though I could be underestimating how well he understands the subject.

I meant more the requirement to use and learn more advanced mathematics from a conceptual point of view. That's the part of math I like--the conceptual understanding. I could care less if a computer does the grinding rather than me. I would prefer there to be much higher conceptualization to grinding ratio in general.

Frankly, every form of engineering has extensive use of simulations and trial and error, and I am quite familiar and experienced doing these. Spice, Modelsim, and Matlab/Simulink in particular.

This stuff bores me to tears.

Astronuc said:
I think jobs that are strictly devoted to symbolic math or equations are few and far between.

In my job, we do simulations which are basically finite element analyses of the thermo-mechancial behavior of solid objects. We use proprietary software developed in-house as well as commercial software like ANSYS, ABAQUS, Fluent, . . .

Part of the development process is to sit down with pencil/pen and paper and derive the consitutive equations, and then cast them into computer code. Then there are an array of thermophysical and mechanical properties models. The theory manual is extensive.

Every now and then we get new data with which to modify an existing model or add a new model. That involves fitting experimental data, or manipulating differential or differentio-integral equations, and casting them into code (FORTRAN).

Our simulations are validated against experiments, and in some cases are used to make predictions, which are ultimately tested by performance or in some cases measurements.

Part of the time we develop methods, but a lot of the time, we apply the methods.

And my colleagues and I are pretty passionate about what we do, and we like to think that it benefits humanity in someway.

The bold-ed part appeals to me (though FORTRAN? really?). I wouldn't mind working on getting the simulations to run and scale really well on cluster machines--that part of coding is a lot of fun for me--making the algorithm match the machine.

I should have mentioned also that this is meant for me to create long-range goals.

Just because I have a computer engineering back-ground doesn't mean I have to stick with computers.

To put it another way:
Having to go back to school to learn something different, may actually be a plus.

For instance this thread makes little sense to me, but learning enough to understand it is very motivating for me.

The thing is, I don't know if GUTs are readily testable--but if they are they seem like they have long-term potential for a great impact on society.
 
Last edited:

1. What is meant by "high impact on society" in relation to scientific research?

"High impact on society" refers to scientific studies or discoveries that have the potential to significantly improve or change the way we live, work, or interact with each other and the world around us. These studies often address important social, economic, or environmental issues and have the potential to shape policies and practices that impact society as a whole.

2. How do scientists test the reality of their findings?

Scientists use various methods and techniques to test the reality of their findings. This can include conducting experiments, collecting and analyzing data, peer-reviewing their research, and replicating their results. These steps help ensure that the findings are accurate and can be replicated by other scientists, further validating their reality.

3. What is the role of logic and symbolic math in scientific research?

Logic and symbolic math are fundamental tools used in scientific research. They help scientists analyze and interpret data, make predictions, and draw conclusions based on evidence. These tools also allow scientists to develop and test theories and models, providing a logical and mathematical framework for understanding and explaining complex phenomena.

4. Can you provide an example of a scientific study with a high impact on society?

One example of a scientific study with a high impact on society is the development of vaccines, which have greatly reduced the prevalence of deadly diseases and have saved millions of lives. Vaccines are a result of years of scientific research and testing, and their widespread use has had a significant impact on society's health and well-being.

5. How does heavy use of logic and symbolic math contribute to the credibility of scientific research?

The use of logic and symbolic math in scientific research adds credibility by providing a systematic and logical approach to data analysis and interpretation. These tools allow for precise and accurate calculations, reducing the likelihood of errors or biased interpretations. Additionally, the use of logic and symbolic math allows for the replication of results by other scientists, further strengthening the credibility of the research findings.

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