Since we have a lot of helpful preeminent professors and researchers here, I would be grateful if they could offer their valuable and insightful advice. Would be grateful to others advising as well! What skills (know-how of programming languages, topics, papers to read(?) etc.) should I brush up on beforehand to be an asset to the school that I end up at? These would include both skills that I would require in case I plan to take up a PhD and skills that put me at the forefront in the job market.

asked 16 Nov '12, 13:06

shadowblade360's gravatar image

accept rate: 0%

edited 16 Nov '12, 14:27

It is a hard question to answer. I think the only correct answer is 'It depends'. First, Grad school and job market(non academic) are different.

Grad school : Programming skill is a great asset. but 'what language' doesn't matter that much. If it is the one your advisor is using, it would be better but, not significantly. High level languages like Matlab, Mathematica are good for academia, usually not good enough for industry. Topic? Do you already have a topic for your PhD? You may have a rough idea but, the specific topic will be refined by your course work, advisor, and a lot of things around you. There is no specific paper to read. Most case, OR faculty want a student with programming skill and Math (or Stat) background (not degree). I mean they are not expecting 1st year PhD student to be an expert in any area.

Non academic Job market : This is more specific. They are not looking for a candidate who has potential only. Language, it should be a specific language that depends on the industry. The same on topic. For example, to get in wall street(finance industry), you better know C/C++, and No arbitrage theory, Stochastic differential Equation an so on. The requirements will be quite different by industry.

Sorry for not giving a clear answer.


answered 16 Nov '12, 15:05

ksphil's gravatar image

accept rate: 14%

Like Phil, I would put programming at the top of my list -- preferably an object-oriented language (C++, Java or Python). I would also recommend getting comfortable with a stats package (how to load data, how to run models, how to generate graphs). For that I would recommend R, partly due to its capabilities but largely due to its price (free, so you don't have to worry whether the school has a license) and its ability to import/export files compatible with other programs.

Familiarity with Google Scholar can't hurt -- you'll be doing literature reviews somewhere down the line.

Soft skills: it's important that you be able to write well, and (particularly if you will be a teaching assistant) it's important that you comfortable with public speaking.

Last, I'd recommend learning enough LaTeX to be able to create and compile documents in it. For a free authoring program that uses LaTeX, I recommend LyX.


answered 16 Nov '12, 17:30

Paul%20Rubin's gravatar image

Paul Rubin ♦♦
accept rate: 19%

For mathematical background, a solid linear algebra course, multivariable calculus, and probability and statistics (for engineers or mathematicians, not the soft versions for business or social sciences). If you can fit in an OR course or two at the undergrad level, that will be helpful as well.

The more programming, the better. If you can fit them in, scientific programming and data structures courses. While the language isn't that important, having exposure to an object-oriented language is good.


answered 17 Nov '12, 16:26

Matthew%20Saltzman's gravatar image

Matthew Salt... ♦
accept rate: 17%

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