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Stat PhD Now Postdoc

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Stat PhD Now Postdoc last won the day on August 15

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  1. I think it is probably fine as long as you mention in your SOP that you took real analysis in your "Advanced Calculus" class and have one of your LOR writers mention this as well. As for withdrawing and taking 5 years to finish, I don't think any of that will affect your chances, and it is not worth mentioning. The grades (especially grades in math/upper division stats classes), letters of recommendation, and test scores are primarily what adcoms look at.
  2. It could possibly help your application to ask one of your LOR writers to mention that you plan to take certain advanced math classes in the spring semester of your senior year (like Real Analysis II and whatever other advanced math/stat classes) to ensure that you are prepared for graduate school. But the most important things are the grades on the transcript you submit with your application (which won't have your spring 2020 grades) and the letters of recommendation. I think you should do well in admissions for most of the schools ranged 16-40 and your chances are above average at Duke and UW (conditional on good performance on the GRE and in Real Analysis and Advanced LA). Penn State has a good reputation, and physics majors who have also taken some advanced math (namely real analysis) are usually looked favorably upon by Statistics adcoms. In fact, an alumnus who just graduated from my PhD alma mater got a TT job at University of Minnesota Statistics (without a postdoc) and his undergrad major was Physics.
  3. Assuming that you score well on the Quantitative section of the GRE and get A's in Real Analysis I and Advanced Linear Algebra, I think you have a definite shot at NC State and possibly Duke. Conditional on strong performance there, I think you could even try applying to a school like University of Washington (though this is possibly a reach). Physics is a hard subject, and your GPA is pretty good. I'd recommend adding a few more schools like Wisconsin or Minnesota too.
  4. OP: The others have already nailed it in their comments, but I would also reiterate that it is not really necessary to get a PhD in Statistics if you want to go into data science (in a non-research role) and you are a U.S. citizen/green card holder. I know people who have gotten DS jobs with only a Masters in Data Science, Computer Science, or Statistics. There are a lot of Stats PhD's who end up going the DS route, but they are typically either: 1) international students for whom a STEM PhD is the most viable way for them to get a work visa in the U.S., or 2) American students who decided that academia was not for them (you'll find a lot of people with not just Stat PhDs, but also CS, math, industrial engineering, and physics PhDs working in this area). If you are certain you do not want to get a research-based position, you probably don't need to get the PhD. If this applies to you, you mainly need to get relevant work experience and possibly a Masters degree (though one of my friends got into data science with only a Bachelor's in Biochemistry -- he did later get an MS in Computer Science, though, which raised his earning potential and allowed him to become a Head of Data Science division at a health care AI company).
  5. I am not really sure what criteria these international rankings are taking into account, but for example, USTC ranks No. 1 in number of papers published in journals with high-impact factor among universities in China (i.e. it has the most papers published in journals like Science, Nature, PRL, JACS, etc. of all Chinese universities). So while its overall ranking may be lower than Peking and Tsinghua, it is particularly renowned for its math and science programs and has a strong reputation for producing successful PhD students in American STEM programs. I suspect that in general, admissions committees in Statistics are far less familiar with reputation and academic rigor from University of Malaya than the other schools that I mentioned, and hence why your chances may be very slim for the very top Stat programs in the U.S. (all of these top programs could easily fill their entire incoming class with just students from the top universities in China and India if they wanted). You can try a few "reach" schools, but I would recommend NCSU as the higher end of the range of schools and generally schools in the top 20-40 of the USNWR rankings for Statistics as the main ones to aim for.
  6. Second the advice above. With your GPA from University of Chicago and those math classes, you should be competitive for most top Statistics PhD programs. If you score well on the Subject GRE, you would have a definite shot at Stanford, but as it stands, I could see you getting into UC Berkeley, Columbia, etc. Having two strong LORs should help your application a lot too. I would recommend only applying to PhD programs.
  7. Is "Advanced Calculus" a course on introductory real analysis? You may want to make it clear in your application. In any case, your profile looks pretty strong, but I would say your chances at CMU, JHU, Michigan, Washington, and UNC are slim, mainly because of the stiff competition from international applicants -- and all the ones from Asia who are accepted into programs at this tier are typically from Peking, Fudan, Tsinghua, USTC, Zhejiang, ISI, SNU, KAIST, KU, and Yonsei. NYU is also a tiny program (less than 10 students total), so it may be very selective as well. I think you should apply to mainly programs at large state universities like North Carolina State University and Texas A&M University (which I didn't see on your list). I think you have a shot at NCSU, TAMU, and Minnesota. I think you also have a decent shot at schools like University of Florida, Florida State University, University of Illinois Urbana-Champaign, University of Connecticut, and Michigan State University. These schools have been known to accept outstanding students from the top universities in Africa, Bangladesh, Vietnam, etc., so I imagine they would also be willing to accept good students from the top university in Malaysia.
  8. Yes, I would also say that it's very possible to get an industry job without any internship experience at all. There are graduates from my PhD program who got jobs at Amazon, JP Morgan, etc. without any internships. If you are leaning towards industry, it might still be beneficial to do one the summer before graduating though.
  9. In my experience, most PhD students in Statistics/Biostatistics do not do internships every summer, nor is it necessary to do one every summer. I have found that it is a lot more common for PhD students to do one internship the summer before they intend to graduate, since satisfactory performance can lead to a job offer for after graduation (and if they decide not to take the job offer, the internship experience can still give them an advantage for the job search elsewhere in the fall). The internship can also clarify if they want to stick with academia and go the postdoc route, if they were on the fence about academia vs. industry. The summer before graduating is also the most optimal time, because most PhD students have finished or are close to finishing at least one project by this point. I don't think the departments care much what you're doing, but I will say that it seems difficult to juggle both research and work. In my opinion, it is better to spend the first few summers studying for the qualifying exams and getting research done (which can take awhile to get started on -- you have to spend at least a few months just reading and familiarizing yourself with the literature of your PhD advisor's research area).
  10. I did a Masters in Applied Math. From what I could gather about PhD admissions at the department, it did seem as though the letters of recommendation were super important, as one poster above said. Grades in math classes were also very important. PhD programs in mathematics also like (domestic) candidates who have already taken a few graduate-level classes (most international undergrad math majors will have taken classes like measure theory, topology, etc. as part of their undergrad curriculum). Since you're from a top school and are taking such courses, you should be in great shape for PhD admissions, provided you score decently on the subject test.
  11. I based my assessment on the rankings, the fact that it is a slightly larger program, and the fact that some of the alumni I'm familiar with from TAMU are also from the top universities in South Korea (Yonsei, etc.). I don't think the fact that your degree is not in Stat is really a problem, as long as your mathematical background is strong -- there are definitely PhD students in Statistics (including international students) who come from an Econ background. But it may help to have your letter writers stress that you took a ton of advanced mathematics like probability theory, measure theory, topology, etc. You can ask them to mention this.
  12. You may want to have one of your LOR writers point out that you retook measure theory in your home institution and got an A and explain the P, as their words carry more weight. This should also be mentioned in your SOP (though I wouldn't say it was because you were "mathematically immature," but put it in a more positive light, like how you were determined to prove to yourself that you could do well in measure theory and were successful to that end). Also, make sure that your letters of recommendation are *very* strong. These make a big difference in getting your application into the "Accept" pile. Your profile looks pretty good, in my opinion. Usually international students from the top 3 schools in South Korea do pretty well in PhD admissions, but the top schools will of course have very, very fierce competition so it helps to apply more broadly. Your list of schools looks very reasonable. You would probably also have a good shot at schools like Texas A&M and other schools of that caliber.
  13. It is hard to gouge your chances at the schools in the 25-50 range of USNWR rankings (I think your chances based on your current profile may be slim for any higher ranked programs), partly because admissions are very competitive for international students. That being said, you definitely need to improve your quantitative score on your GRE in order to have a chance. The B's you received in Analysis and undergrad probability are also potentially concerning. I would recommend applying to mainly Masters programs in Statistics (not Applied Statistics, Data Science, or Data Analytics programs -- make sure that the progrms you apply to explicitly require a year-long mathematical statistics sequence taught at the level of Casella & Berger, as well as a course on the theory of linear models) and using that as stepping stone for PhD applications. It may be worthwhile to also retake Analysis in your MS program to get an A or A-. Do well in a MS program, and you can likely get into some program in the range of UMinnesota to Temple U for your PhD.
  14. Agreed with the others that you should do a bit more research. For example, University of Florida does not have an official Masters program in Statistics, only a PhD program with a Master of Statistics "along the way" (some students exit with only the Masters). OP: Being an international student, if your goal is to ultimately work in the U.S.A., the PhD is your best bet. Even if you plan to go work in industry as a data scientist, it is currently very hard for international students to get these jobs in the U.S. without a PhD in a quantitative field (doesn't have to be Statistics, it could also be math, computer science, physics, industrial engineering, etc.). American citizens and Green Card holders can usually get such jobs easily with only a Masters (and sometimes only a Bachelor's), but the bar is higher for noncitizens. An MS in Analytics may not cut it for an international student to get a job in the U.S, nor would it help for PhD admissions down the road. I would apply to mainly PhD programs if I were you, and Masters programs in traditional Statistics which could make you more competitive for PhD admissions at mid-tier programs if you perform well.
  15. Berkeley and UMich may be difficult to crack, especially since you are an international student (there is much more competition). If you want to try a "reach" school, I would recommend NCSU or UWisc. The others on your list seem reasonable targets, provided that you do well in Real Analysis. I would add more schools ranked at or below the level of UCLA to your list.
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