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Cryolite

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About Cryolite

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  • Application Season
    2013 Spring

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  1. So, I've narrowed it down to two schools that I'm considering. I'm a math major who wants to go to graduate school. Georgia Tech ACO gave me a PhD admit in mid-February, and Stanford ICME gave me a masters admit in mid-March. While the masters admission would normally be out of the question, I recieved an NSF GRFP, so all of my funding problems are gone; I can continue to the PhD program and get a TAship at Stanford as normal once my NSF funding lapses. So here are the pros and cons: Stanford: Pros: Prestige Excellent body of researchers in fields other than applied math (which is what I was accepted for) Good coursework Nice faculty to work with; most of them were approachable. Job placement It's Stanford Cons: No graph theory (the field of math I would like to work in most) Not as good an advisor as the one at Georgia Tech Georgia Tech: Pros: The best graph theory program in the country An excellent advisor who seems enthusiastic to work with me (he offered me an RAship before I got my NSF GRFP) Similarly nice faculty to Stanford Very well known in the field Cons: Not as much prowess in math other than graph theory (the rest of their program is good but not great) Coursework is less intensive, but similar to Stanford for the most part Job placement is significantly worse here A little bit about myself: Undergrad: unranked, unknown state; majoring in math w/ econ minor GPA: 3.8 overall, 3.9 in core Research: I've done a couple independent studies on analytical number theory and a research project on integral equations, which ended in a paper. I've also done an REU on computational geometry which resulted in an unpublished manuscript (I'll publish it when I have time) and I am currently doing a senior thesis project on saturation numbers with a pretty well-respected professor. Interests: pretty flexible; I'd prefer to do graph theory or other combinatorics but I will willingly work in applied math as well. TA experience: 1 semester of grading and 1 semester of tutoring Scholarships: Nothing special; dean's list, departmental stuff, the like. GRE: 169 Q 166 V 5.0 W; 800 (81%) subject Other: I have an NSF GRFP; 30 on putnam So, what should I do? I really have three options: 1.Accept Georgia Tech 2.Accept Stanford 3.Accept Stanford for MS, and defer Georgia Tech for a PhD (this might raise problems with the NSF)
  2. Cryolite

    Picking a Math PhD Program

    UPDATE: CMU is out too. Georgia Tech is better for what I want to do. So there are two schools left: Georgia Tech or Stanford. I'm leaning toward Stanford. Any advice, guys?
  3. Cryolite

    Picking a Math PhD Program

    UPDATE: UIUC is also out. It was a very tough decision, but I finally reached the conclusion that the research that goes on there was too limited; there was too much of a risk of finding all of the projects boring and leaving. Also, most of the good professors there have five or six people working with them already, so it is likely they won't have time for me.The final nail in the coffin was the fact that UIUC's math department does not have a great pipeline into industry jobs (which is where I'm leaning right now). That leaves three schools: Stanford, Georgia Tech, and Carnegie Mellon. I should probably elaborate why I haven't picked Stanford immediately. Georgia Tech is the 4th best discrete mathematics school in the country (according to US News), and in the field of discrete math I want to work in (graph theory), they're probably second only to UCSD. CMU isn't far behind, at about 5th or 6th by my estimate. In addition, the program I got admitted to at both Georgia Tech and Carnegie Mellon (ACO) is a combination of discrete math, computer science, and either industrial engineering or management respectively. Both schools are top 10 in either of the disciplines ACO covers. But the real reason I haven't been able to choose Stanford immediately (and the reason I'm leaning away from CMU, since I don't have this same advantage) is that I already have a professor at Georgia Tech who is willing to work with me. He is probably the best person to work under there, and he is known as one of the best people in graph theory right now. So, that's where I am. All three programs are very good, but they all have entirely different advantages.
  4. Cryolite

    Picking a Math PhD Program

    Yeah, Stanford said that while they don't fund any masters students, they will fund all PhDs. So, once I enter the PhD program (entry is guaranteed with research, quals, and a high enough GPA), I will get a TAship and tuition waiver in the PhD. In total, the NSF functions as a 3-year fellowship with a TAship afterwards.
  5. Cryolite

    Picking a Math PhD Program

    UPDATE: NYU said they would consider me for funding in their PhD program after I consider their masters program. However, talking with the head of the masters department revealed that only 1 or 2 masters students successfully transfer to the PhD program. Because funding is not guaranteed even then, I am removing it from consideration. This leaves 4 schools, which in order of current leaning is: Stanford, Georgia Tech, Carnegie Mellon, UIUC. Also, in response to the poster above, I like the research at Georgia Tech best, although it's very close. The people at Stanford are doing great things with estimating the solutions to systems of equations, and Carnegie Mellon does a lot of interesting stuff too. Urbana-Champaign probably has the least interesting research, but they still are doing some nice stuff. My research interests are fluid enough so that research can't be the only factor in making a decision though.
  6. Well, I've got some decisions to make. At this point, I have acceptances at 4 schools: Stanford ICME, NYU, Georgia Tech ACO, and UIUC. In addition, a personal email from Carnegie Mellon's graduate director makes me think I have a 90% or so chance of getting in there as well (for ACO). NYU and Stanford offer me masters-to-PhDs, and normally these would be out of the question. However, I recieved an NSF GRFP fellowship, and thanks to the fellowship paying for three years of school, I can get waived tuition at a masters and continue to the PhD program normally. Stanford specifically told me that they fund MS-to-PhD students with TAships once they finish their masters and pass quals. However, I have seen no such guarantee from NYU. Will they fund me after year 3? A little bit about myself: Undergrad: unranked, unknown state; majoring in math w/ econ minor GPA: 3.8 overall, 3.9 in core Research: I've done a couple independent studies on analytical number theory and a research project on integral equations, which ended in a paper. I've also done an REU on computational geometry which resulted in an unpublished manuscript (I'll publish it when I have time) and I am currently doing a senior thesis project on saturation numbers with a pretty well-respected professor. Interests: pretty flexible; I'd prefer to do graph theory or other combinatorics but I will willingly work in applied math as well. TA experience: 1 semester of grading and 1 semester of tutoring Scholarships: Nothing special; dean's list, departmental stuff, the like. GRE: 169 Q 166 V 5.0 W; 800 (81%) subject Other: I have an NSF GRFP; 30 on putnam So, what do I do? Thanks for your help in advance
  7. Cryolite

    Keep A Word Drop A Word

    Yellow Jacket
  8. Cryolite

    Keep A Word Drop A Word

    Chaos Emerald
  9. A nation should require all of its students to study the same national curriculum until they enter college. Should a nation require its students to all learn the same material until college? Some would state that a nation should require every student to learn the same material in grade school, as this guarantees that every student has an identical opportunity at education. Others would claim that instituting such a policy is counterproductive, as every student has his or her individual needs and preferences that a national curriculum would not be able to provide. After weighing the evidence, it is clear that a nation should not force all of its students to learn the same national curriculum. Every student is unique and therefore would be best educated in a system that treats them as such. Those that would argue that a nation should require its students to learn the same material until they enter college might claim that instituting a national curriculum would guarantee every student would have an identical opportunity to learn and therefore and an identical opportunity at success. This argument is certainly plausible, but does it truly show that instituting a national curriculum is optimal? Such a program would likely satisfy the educational requirements of the average student, but a national curriculum would also not satisfy the demands of those students who are not average; those with educational disabilities or who are exceptionally gifted. A program such as this would lead to an optimal education for the average student, but would fall short on educating everyone else. Thus, a nation that requires its students to all learn the same material would educate the average student best while neglecting those at the edges, which can hardly be seen as an optimal arrangement. Now, consider the opposite side. Educating students based on individual needs would allow the needs of students with special needs, such as the aforementioned gifted and students with learning disabilities, to be educated better, while also allowing the average student to recieve the same education that would be provided by a national curriculum. Educating students in a system such as this would not significantly affect the education of students close to the average while also improving the education of those who are not average. Improving the education of those not average students will lead to a better, more productive society. For example, Albert Einstein was seen as a poor, unmotivated student in school. He barely passed his high school, but when he left the grade school system, he obtained a PhD in physics and went on to win a Nobel Prize. During his grade school, where he was pidgeonholed like everyone else into learning the same material, he was a poor student, but when he went to college and recieved an education more suited to his needs, he blossomed and became the most recognized scientist of the 20th century. In conclusion, it is clear that instituting a national curriculum is not optimal; a program that treats students on a case-by-case basis would be far more beneficial. A national curriculum would provide a good education to students near the average but would be inadequate.
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