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Scientific Computing vs Applied Math at UMN

  1. Oct 5, 2015 #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 Research

    The 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.
  2. jcsd
  3. Oct 11, 2015 #2
    Thanks for the post! This is an automated courtesy bump. Sorry you aren't generating responses at the moment. Do you have any further information, come to any new conclusions or is it possible to reword the post?
  4. Oct 11, 2015 #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.
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