Stat Assistant Professor

Undergrad statistics coursework is not that important for PhD admissions, though it could potentially be helpful to have taken an undergrad class in Calculus-based probability and an upper-division undergrad class in statistical inference. I know people who got into Stats PhD programs who had never taken a statistics course before matriculating (they had a lot of math though). I think you would get into a top 10 masters program in Stats, no question. However, that would entail dropping a lot of money on something that isn't required for you to get into a decent PhD program. I also think it would only make you marginally more competitive for PhD admissions at the top programs, unless you got something *really* noteworthy out of it (e.g. a publication in a respectable journal).

I think you are selling yourself a bit short. You could apply directly to PhD programs and probably get into a top 20 Stats PhD program (think: University of Minnesota, Texas A&M, Penn State). You might even get lucky and get into a school like Carnegie Mellon or University of Washington. There's not much to be gained from getting a Masters in your case if you are mainly interested in getting a PhD. I would only recommend Masters degrees for students who are only seeking a terminal degree in Statistics, who didn't have the best math grades in undergrad and need to "atone" for their undergrad performance, or who didn't major in math/a quantitative subject in undergrad (I would also recommend Masters for international students who did not attend well-known undergrad institutions in their home country). None of these applies to you. I would recommend that you get recommendation letters from the professors that you did research with and one letter from a math professor who can attest to your mathematical abilities. I think you will have good results if you just apply to Statistics PhD programs directly.

If you're only considering the top stat/biostat programs, I wouldn't say there is much difference between them (stat vs. biostat) in terms of quality, training, or placements. For example, Harvard Biostatistics and Johns Hopkins Biostatistics have both placed exceptionally well not just for Biostat departments but also for Statistics departments. For example, these guys have PhDs from JHU Biostatistics and they publish a ton of work in top methodological and theoretical statistics journals: https://sites.stat.washington.edu/people/fanghan/ https://yangning.stat.cornell.edu/ Of course, JHU and Harvard Biostat also have very good placements of their graduates as TT faculty in other Biostatistics departments too.

Statistics departments tend to be a bit more theoretical than the majority of biostatistics departments. The top 5 biostatistics departments will have more theoretical coursework as well as more theoretical research (e.g. UW, Hopkins, Harvard, and UNC Biostats all have faculty who publish regularly in journals like Annals of Statistics and JASA-Theory & Methods and who serve on those journals' editorial boards). But for biostatistics, the further down the rankings you go, the more applied the department will be. Additionally, most statistics departments fund their students through teaching assistantships (though some statistics faculty who have a lot of external funding can support their students as research assistants), whereas biostat departments usually fund their students through RAs and external grants. This is in part because there typically aren't undergraduate biostatistics majors, whereas TA's are needed for undergrad statistics courses. It's not always so "cut-and-dried" though. You can do a mostly/entirely applied statistics dissertation in a Stat department, even ones that are known to be more theoretical (e.g. I know a few people from UPenn Wharton who wrote applied stat dissertations with little to no theory). And you might be able to do a more theoretical PhD at a biostat department, especially at a top one (one of my postdoc supervisors did his PhD work at Johns Hopkins Biostatistics on statistical theory for generalized estimation equations). Your profile would be well-suited for either the top statistics or the top biostatistics programs. I suppose it depends also on your research interests. If you really enjoyed working on genomics, you could target programs that have strong faculty in statistical genetics (e.g. University of Michigan Biostatistics or UPenn Wharton Statistics -- at Penn, you could work with Nancy Zhang and Hongze Li). If you really enjoyed your theoretical math classes and wanted to keep doing similar stuff like that in statistics, you could focus primarily on Stat programs, with a few of the top Biostat programs thrown in there.

I think ETS is giving people the option to take the general GRE at home instead of in testing centers. I believe Stanford has waived the math subject test requirement, though, since that is only offered as a written exam. But then again, Stanford is the only program I'm aware of that required the math subject GRE before this year (some programs recommended it, but I've heard of people getting admitted to top programs without it).

Your profile looks very strong. If you attended a top 3 university, I don't think it matters whether there is "grade inflation" or not. You have also taken a lot of graduate-level courses in both math and stat, and grades in grad school tend to be inflated anyway. Your research experience in evolutionary genetics is also a plus. I think you should apply to mainly top 15 stats programs (according to the USNWR rankings). I'm sure you will get into several of them.

I know a few Stanford alumni/students who published research that they had done as an undergrad (not their PhD research) in JRSS-B or Annals of Statistics -- often their work appeared in these venues during the first year in their PhD program. That is quite uncommon though, even for Stanford -- but it's not terribly surprising that a small number of folks at Stanford already have top-tier papers so early in their research careers, before they have even finished all their PhD coursework requirements. I think it's more common to see international PhD students with papers in journals like "Statistics: A Journal of Theoretical and Applied Statistics," "Journal of Statistical Computation and Simulation," or "Journal of Business and Economic Statistics." I've seen this from a lot of Stat PhD students from South Korea.

I imagine you will have no difficulty getting into any Masters program in Biostatistics, provided your GRE Q score is sufficient (aim for over 160, ideally over 162). If you are contemplating getting a PhD later down the road, I would recommend taking a semester of Real Analysis in your Masters program (I don't see that you have taken this class, and at least one semester of it will be required for most good Biostat PhD programs).

Lack of statistics courses is not an issue for admissions to graduate school in Statistics. Math courses are much more important, and programming skills are helpful. You've got those covered quite well. I would recommend applying to mainly top 20 programs. I foresee you being admitted to a very good school.

PhD admissions for international students is very competitive, and your math background isn't as deep as a lot of other international applicants (although you attend a good college in the USA). I think you could probably have a chance at schools in the range of Purdue to UConn. Programs higher than that might be a reach (only because of the competition for international students), but I would recommend trying a few programs ranked higher than Purdue and then mainly focus on applications in the range of Purdue through UConn, with a few lower ranked schools for good measure. In addition, larger state schools are probably more likely to accept you than smaller programs that may not be ranked as highly but are very small and hence selective (e.g. UVA, Northwestern, and NYU are smaller programs, while Ivy League programs are very selective, regardless of their USNWR rank, etc.). So I would also focus attention on bigger programs at flagship public universities.

I think you can likely get into a Masters program with your current profile. Your math grades aren't the best, but they're mostly above threshold, and your GPA is also above the minimum threshold. Your Quantitative GRE score is a bit on the low side for Stat though. If possible, I would recommend retaking it to get a few points higher (163+).

Your profile is very strong, and I think you can get into top Statistics programs if you secure strong letters of recommendation. A triple Math/Stat/Physics major with a 4.0 from JHU will look very impressive to admissions committees, and your research experience is also a plus (especially in a subject as difficult as physics). I would recommend getting at least one letter of recommendation from a math professor. You don't need to have conducted research or independent study with them. They just need to say that you are a very strong student with high mathematical aptitude. I would go with one letter from a math professor, one from one of your physics research advisors, and one from your applied math research advisor (the one with whom you're working on PDEs/differential geometry).

Having a publication would make your profile even stronger, of course. I would try to find out the profiles of other students from your university who have enrolled in PhD programs in the U.S. in recent years (including where they ended up matriculating), to see how your profile measures up compared to them. I think you will ind a decent number of Korean students with some publications. However, even without research/publications, I do think you are competitive enough to get into good programs in the 20-40 range at present, and you could get lucky and get admitted to a top 20 program or two as well... I just think you need to apply to a lot more schools in the 20-40 range to maximize your chances of getting in somewhere.

You have a strong profile, but I wanted to give some anecdotal evidence. I know several native Korean students who got their PhDs at schools like NCSU and Texas A&M, and they ALL had publications in statistics journals before starting their PhD program. It seems as though the profiles of students from the top schools in South Korea are especially impressive, and thus, the competition is probably a lot fiercer. The one person I know who got his PhD at NCSU even had *several* publications in stat journals and had worked as a lecturer in statistics (he had a Masters degree in it already from South Korea) before starting his PhD at NCSU. Based on this, I would recommend adding more schools in the 20-40 range (according to the USNWR rankings). I think you could definitely get into a school like University of Florida, OSU, or UIUC, but you might also get lucky and be admitted to schools in the top 20. Good luck!

I would not choose a research area based on trying to "maximize" your chances of getting hired. A department's perception of your research "fit" is just not one of those things that you can control, and departments' needs change from year to year. For example, if the department's only probabilitist or ecological/spatial statistician is retiring, then the department may want to hire a new Assistant Prof who is a probabilitist or a spatial statistician. There were some departments I applied to that wanted to hire more Bayesians because their department currently didn't have that many people working on Bayesian statistics, and there were others that were already overwhelmingly Bayesian and they wanted to keep it that way (so they only had campus interviews for people working in Bayesian statistics). The best way to maximize your chances of getting some interviews is to apply to a wide number of schools (to account for the things beyond your control) and to put together a strong application (i.e. strong CV/publication record, strong research and teaching statements, and strong recommendation letters).

The job candidate did go to one of the top 15 schools (according to the USNWR rankings). And yes, that person's profile is *especially* good. I will also note that during the the 2019-2020 hiring cycle, some people got campus interviews at the likes of UPenn Wharton, Columbia, Cornell, etc. with more on the order of 5 or 6 papers, though (and the candidates weren't all from Harvard, Berkeley, Stanford, etc. either, but some were from schools like UC Davis and Rice University). But the publications they did have were in top venues. One of the people I'm referencing had 1 paper in Biometrika, 1 in JRSS-B, and 1 in Annals. For R1's, there are usually a few 'superstar' job candidates that will get 15+ interviews (including at all the top programs), and then for the rest of us, it is a combination of research record and luck.

6 total papers, I think... 5 of which were accepted/published (the other one under review) and one of which was in Annals of Statistics. As I said though, it isn't just about having some number of papers. It also depends on things like your research area and other factors beyond your control. If the search committee is, for instance, prioritizing applications from job candidates working in environmental/spatial statistics (say) and that isn't your research area, then you won't be hired no matter how long your CV is. If the department just recently hired somebody with very similar research as you, then they may opt to go with other job candidates who can "add something new" to the department. Search committees may also have their own preferences -- for instance, a member of the search committee might be really good friends with a job candidate's PhD or postdoc advisor, and they will forcefully advocate for that job candidate. It's stuff like that.

It should look something like this guy's webpage: http://www.travisfreidman.com/ Notice how he has his teaching philosophy, teaching goals, teaching competencies all very visible on his site. He also has a page for his teaching evaluations, including summary statistics, and he has the syllabi and course materials for the courses that he has taught. Your site should really sell your abilities as a teacher. If you were to apply to a research university, you don't need to include as much (or anything, really) about teaching. A more "typical" webpage for someone seeking an R1 job would probably be something more along the lines of this: http://web.stanford.edu/~songmei/

The elite LACs also care a lot about teaching, even if their research expectations might be somewhat higher than a "typical" PUI. So if you are aiming for an elite LAC, you should definitely try to obtain teaching experience. I recommend that those who are aiming for jobs at PUI's create a personal webpage that highlights teaching experience (e.g. you should put examples of your teaching evaluations or a "teaching portfolio" on there). Those aiming for jobs at research universities should emphasize the research aspect on their personal webpage.

Yes, looking at the CV's of recently hired Assistant Professors at these schools is a good way to get some "baseline." It's not a clear-cut set of criteria for TT jobs, so you don't need [x] number of papers, exactly. It's more like if you have *at least* one paper in a top journal AND your research area is something that the department is interested in (so for example, a probabliitist with a very prolific record won't get an interview if the department isn't interested in hiring a probabilitist), then you will usually make it past the initial cut where they trim down all the applications into a set of 20 or so that they look at more carefully. And the more papers you have in top journals, the fewer *total* number of papers you need (for example, an Assistant Professor at UPenn Wharton who joined the department in 2019 had "only" four papers, but three of them were in Annals of Statistics). I don't think working with an Assistant Professor is necessarily an issue. There was one job candidate on the job market in the 2019-2020 hiring cycle who got like, 20 interviews, and her advisor was an Assistant Professor. She also got offers from UIUC, UNC, UFlorida, UMinnesota, Columbia, and probably others as well.

For jobs at R1's (and R2's to a lesser extent -- though R2's do seem to care more about teaching and have a typical teaching load of 2-2), your publication record and your letters of recommendation are the most important aspect of your job application. Teaching doesn't matter as much, though you should put some thought and effort into the teaching philosophy. Most R1s ask you to submit a teaching statement, but it generally won't be given as much weight as the research. It's not necessary to have teaching experience to land an AP job at an R1. If you get a campus interview at an R1 or R2, they most likely won't make you do a teaching demonstration, whereas a PUI or a lectureship position would definitely make you do one. Yes, it is possible to go straight from PhD to Assistant Professor, but your publication record would need to be especially strong in that case. One of my PhD classmates got an AP job at UMinnesota without a postdoc, but he had six papers by the time he graduated, including one in Annals of Statistics. If you have two or more papers in JASA, Annals, Biometrika, JRSS, Biometrics, etc. as a PhD student, then you could probably bypass the postdoc. Of course, the top journals count for more, so if you have two papers in Annals/JASA/JRSS/Biometrika, then you might be competitive with "only" three or four papers total. I did not have any papers in the very top journals from my PhD, but got two either accepted or invited revision at JASA from my postdoc. So that helped make my profile a lot stronger.

For tenure-stream faculty at business schools, it is also mainly research-oriented, with a typical teaching load of 2-1. A typical tenure-stream professor in a business school would teach maybe one undergrad class and one MBA class, and they usually teach the same class(es) from year to year. The rest of their time is spent on research and service.

I don't think it is necessary to involve undergrads in your PhD research. I know several faculty at PUIs and none of them did this for their PhD/postdoc. It's more that your application needs to convey that you understand that the main purpose of a PUI is centered around the undergraduate experience and education. So you should be able to come up with some project ideas that can involve undergrads. Lecturer positions do not require any research at all (and hence, there are a lot of lecturers at math and stat departments who only have Masters degrees). A TT position at a four-year college will have at least some research/publishing requirements. But at a PUI, the teaching load would typically be anywhere from 2-2 to 4-4, so you aren't expected to do as much research (unless you're at a prestigious school like Amherst College). They actually want you to spend most of your time on teaching and service to the department/college. As for service, I would not expect most faculty applicants for AP jobs to have a lot of meaningful service to a university. But I do think PUIs would be very partial to applicants who have done some sort of mentoring (e.g. participating in a summer program where you taught a short course to students, programs where you mentored students from underrepresented groups in STEM, etc.). Diversity is a plus for any type of faculty job, at both research universities and PUIs. I don't think industry experience matters all that much. PhD institution doesn't matter as much as publications, letters of recommendation, and teaching experience, and in Statistics, that's true for either research universities or PUIs. The caveat to this, of course, is that people from more prestigious institutions are more likely to have more competitive profiles (especially for research).

Lecturer positions at research universities are not tenure-track but are usually fairly secure. At my PhD institution, all the lecturers were able to renew their contracts. It seems like a sweet gig if your passion is teaching. I would have to say that "teaching assistant professors" (i.e. that are tenure-track) are indeed extremely rare. If you want a TT job that prioritizes teaching, you should look for jobs at PUIs -- that is, liberal arts colleges and regional state schools that do not award doctorate degrees. It is a buyer's market though, so even these institutions will want to see some publications, and a lot of newly hired stats faculty will have done a postdoc. You would still need to publish as an Assistant Professor at a PUI, but the publishing requirements would be considerably lower than at a research university for most of these schools (outside the very elite SLACs). Interdisciplinary articles also count towards tenure, and papers written with undergrads are especially well-received. The main criteria for tenure is teaching and service, though. To be competitive for these jobs at PUIs, you should have some publications in respectable venues (not necessarily the top ones like Annals or JASA, but ones in places like Computational Statistics & Data Analysis, Scandinavian Journal of Statistics, etc.) and you should have taught at least one class as an instructor of record. Many PUIs ask you to submit teaching evaluations with your application, and they pay special attention to the cover letter and the teaching philosophy. So you really need to convey in your application materials your passion for teaching and how you can involve undergrads in your research. The search committees are always trying to weed out any applicants who aren't serious about the school's mission and who view the job as a "backup" or as a "stepping stone" to a job at a research university. The campus interview for lecturer positions and AP positions at PUIs also always includes a teaching demonstration, so you would need to prepare for that (in addition to a research job talk if the job is tenure-track).

After you updated your post with your info, I would have to agree with the posters above that your profile is very strong. You could probably apply to all top 10 programs, and I'm sure you would get into at least a few of them. UC Berkeley and UW definitely seem plausible, as does Stanford if you can score well on the Math Subject GRE. If you are more flexible about your geographical preferences, you could probably get into really good schools on the east coast or midwest as well.