Scientific Computing vs Applied Math at UMN

In summary, the conversation revolves around the individual's academic background in Computational Physics and their interest in pursuing a graduate program at UMN. They are considering two options: Scientific Computing M.S and Applied Math M.S. They seek clarification on the differences in career opportunities between the two fields and whether a PhD is required for jobs in these fields. The individual also expresses their preference for a career that utilizes numerical analysis and mathematical modeling. Overall, the Scientific Computing option is seen as more generic with a wider range of job possibilities, while Applied Math is viewed as more specialized with limited job opportunities.
  • #1
malignant
42
1
I'm graduating this year with a B.S in Computational Physics (the difference is the second semester upper division physics courses aren't required, and are replaced with a year of numerical analysis and a CS minor. But I took the 2nd semester physics back when I was a physics major anyways) and am looking to transfer to UMN.

I'm currently torn between UMN's Scientific Computing M.S and Applied Math M.S. I suspect me being torn stems from not really understanding how the career opportunities differ. I would like to work in industry preferably in a field that uses a lot of numerical analysis and mathematical modelling (I'm comfortable using languages such as Python, C++, Java, etc). I would be OK with something in finance as long as it utilized my interests. I'll describe the two programs and it would be helpful if you guys could help me understand what type of careers these two fields would prepare me for.

For the scientific computing program, it says it requires 28 course credits and 10 thesis credits. 8 of the course credits must be in scientific computing and I guess the rest can be more in scientific computing or courses in one of the supporting departments (I would pick a good amount in math).

The courses offered in scientific computing are:

SciC 8001 Parallel High-Performance Computing
SciC 8011 Scientific Visualization
SciC 8021 Advanced Numerical Methods
SciC 8031 Modeling, Optimization, and Statistics
SciC 8041 Computational Aspects of Finite Element Methods
SciC 8090 Topics in Scientific Computation
SciC 8095 Problems in Scientific Computation
SciC 8190 Supercomputer Research Seminar
SciC 8594 Scientific Computation Directed ResearchThe courses that can be picked from the math department for the scientific computing program are:

Math 5467 Introduction to Mathematics of Image and Data Analysis
Math 5485 Introduction to Numerical Methods I
Math 5486 Introduction to Numerical Methods II
Math 5487 Computational Methods for Differential and Integral Equations in Engineering and Science I
Math 5488 Computational Methods for Differential and Integral Equations in Engineering and Science II
Math 5535 Dynamical Systems and Chaos
Math 5651 Basic Theory of Probability and Statistics
Math 5705 Enumerative Combinatorics
Math 5707 Graph Theory and Non-enumerative Combinatorics B
Math 8441 Numerical Analysis and Scientific Computing I
Math 8442 Numerical Analysis and Scientific Computing II
Math 8445 Numerical Analysis and Differential Equations
Math 8450 Topics in Numerical Analysis
Math 8571 Theory of Evolutionary Equations

As for the Math M.S, it requires 20 course credits, 14 in math and 6 in another field (another field as in CSE, Scientific Computing, etc) and then 10 thesis credits.

Anything can be chosen from the math program including pure math classes not listed above but I would pick applied math courses.

So my question is, what is the differences in career opportunities in these two fields? Do they both have a good chance in financial modelling or do employers prefer one over the other? Do jobs in these fields usually require a PhD? I'd be interested in hearing about any careers that use these types of skills.
 
  • #3
I don`t know for sure, but off the top of my head, I think the Scientific Computing option would be the more generic of the two and, therefore offer the most job possibilities. I suppose it depends on location, and industry you want to be in.

The first thing that comes to mind when I think of Applied Math is some egghead locked up in a back office doing weird abstract math, very specialized and with few job opportunities (sorry Applied Mathematicians-- it is my immediate gut reaction.)

The first thing that comes to mind when I think of Scientific Computing are a host of possible fields: aerodynamics, structural analysis, chemical reactions, industrial processes, signal processing, game development, optimization, etc. -- a much wider range of activities.

Again, this is just my immediate, off-the-top-of-my-head, opinion. You might be in a part of the country where the reverse is more common.
 

1. What is the difference between Scientific Computing and Applied Math at UMN?

Scientific Computing at UMN focuses on the development and application of computational methods and tools to solve complex scientific problems, while Applied Math at UMN emphasizes the use of mathematical theories and techniques to model and solve real-world problems in various disciplines.

2. Can students major in both Scientific Computing and Applied Math at UMN?

Yes, students can pursue a double major in Scientific Computing and Applied Math at UMN. However, it is recommended that students discuss their plans with an academic advisor to ensure they can fulfill all requirements for both majors.

3. What types of courses are offered in Scientific Computing and Applied Math at UMN?

Both programs offer a range of courses in topics such as calculus, linear algebra, numerical analysis, differential equations, and programming. Scientific Computing also offers courses in scientific computing methods, data analysis, and scientific visualization, while Applied Math offers courses in areas such as mathematical modeling, optimization, and statistics.

4. Are there research opportunities available for students in Scientific Computing and Applied Math at UMN?

Yes, both programs offer research opportunities for students. Scientific Computing students can participate in research projects with faculty in areas such as computational fluid dynamics, astrophysics, and bioinformatics. Applied Math students can work on research projects with faculty in areas such as mathematical biology, operations research, and climate science.

5. What career paths can students pursue with a degree in Scientific Computing or Applied Math from UMN?

Graduates from both programs are well-equipped for careers in industries such as technology, finance, and healthcare, where there is a high demand for individuals with strong quantitative and analytical skills. They can also pursue graduate studies in fields such as computer science, data science, or applied mathematics.

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