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Found 116 results

  1. I've heard of a lot of people who applied to University of Michigan's Biostatistics PhD program and got offered admission to their MS to PhD fast track. My question is should I apply for just the MS, just the PhD, or both programs if I want to get that fast track offer? I'm a molecular and cellular biology major, with a little higher than a 3.7 math GPA (only took "multivariable calc" and "intro to statistics and probability and the associated lab", and I'm taking linear algebra this fall, maybe another math class spring semester). I also saw on the UM website's tableau graph that around 70% of applicants get into their MS program. Am I just imagining that?
  2. jjj02027

    PhD applicants: Fall 2018

    Hi, Thought I'd start this topic for 2018 fall applicants specifically for Public Health. I realise there is a general one for all applicants, but thought it might be useful to have one for just a Public Health field (in the most broad sense). I apologise if this post is redundant. I just wanted comments on whether my choice of universities were too strong. Although these were the only programmes which matched my interests. Feel free to comment/share your experience so far. Undergrad Institution: Imperial College London, UK (Top for science in UK)Major(s): Biomedical SciencesMinor(s): n/aGPA in Major: no GPA system in UK (Upper 2nd class)Overall GPA: n/aPosition in Class: Type of Student: International female Postgrad: MSc in Public Health (GPA 3.88) at London School of Hygiene and Tropical MedicineGRE Scores (revised/old version):Q: 160 (76%)V: 167 (98%)W: 4.5 (82%)B:TOEFL Total: n/aResearch Experience: 2 years in health services researchAwards/Honors/Recognitions:Pertinent Activities or Jobs: some teaching assistanceAny Miscellaneous Accomplishments that Might Help:Special Bonus Points:Any Other Info That Shows Up On Your App and Might Matter:Applying to Where:Harvard, John Hopkins, UNC, UCLA, UCSF, Northwestern, Brown, Ohio State, Iowa, Standford
  3. Hi everyone, It's near April 15 now. And I still can't decide on this two programs. --- UNC pros: Higher rank in biostatistics, and better location (triangle area). I do believe UNC is more than well-regarded in this field. Does it mean their student will have better opportunities in finding academics and industry jobs? UNC cons: As an international student, I still haven't received any funding. And it looks like it has always been a problem for UNC. To me, it kills the creativity when you have to worry about money in PhD life. --- UW Madison pros: It's full-funded. The curriculum of UW Madison seems legit to me. They provide 3 course sequences in Biostatistics Theory and Methods, Computer Science, and some Specialization Topics. I really like the CS sequences, because I'm major in Statistics now, and didn't get much CS training, which I think will be of huge importance in graduate study & research. UW Madison cons: As opposed to the UNC pros, it's not as highly ranked. The location and weather are not as good I guess? And it is a new program. I literally can't find any insider's experience. There are too many uncertainties. --- Any thoughts on this two programs? Please help me, any comments or thoughts will be much appreciated. Thanks!!!
  4. Hey everyone! I am admitted to MS biostatistics programs at UNC and Michigan. Both schools have an internal process and a preference of admitting their own master’s students to their own PhD program, especially UNC. I was wondering would it be bad if if apply for an internal transfer as well as trying to apply for other TOP biostatistics programs like Harvard or JHU in the meantime? Would it be a bad impression for the faculties? Thank you!
  5. Hello all, So my name is John Thomas, rising senior at Ursinus College. I am doing undergraduate research at both Ursinus and Temple, and doing an internship at a national taste testing facility known as RDTeam. I created my own major in Statistics here and am the first of my kind. Starting out as Bio, I had grades in the mid 2's , speaking GPA. I have climbed up to a 3.12 cumulative and will be taking probability in the fall. This is also when I will be applying but my fear is that I will not be considered since I will not have taken 3 courses in my major (Differential Equations, Mathematical Statistics, and Linear Regressions) at the time of my application. I would ideally like to get into a PhD program right out of college but I fear without these courses on my transcript I will not be able to. What are some ways I can overshadow this, or should I just put all my marbles into starting out as a Masters student? Also, if anyone has any east coast theoretical statistics programs, please list! Thank you all -John
  6. Hello! I've been accepted into Columbia and UNC's Biostatistics MS programs and I'm having trouble deciding between the two! I'm leaning towards Columbia but it worries me that their Stats department is apparently not well regarded. Does this reputation extend to their Biostats department, even though their department is still in the top 10? I know that UNC is a better program overall and has more renowned professors, but if my end goal is to pursue a PhD, does it matter where I get my MS? Cost is not a strong factor because I consider living in NYC to be a once in a lifetime opportunity. I am also more interested in eventually working in industry if that helps. (I've heard that Columbia has more ties in industry and UNC is more theoretical with difficult quals) Thanks so much for any replies!
  7. So I received a PhD offer from UNC Biostats last week, yet the offer letter did not mention funding details and says 'funding will be determined separately'. I looked through several threads about UNC biostats from last year, and found some applicant admitted to UNC biostats PhD program seems to be unfunded (at least until last March, the date that thread was posted). I am an international student and I feel it might be more difficult for me get funded, so I am a bit worried, and wanted to ask if anyone knows about the funding opportunity at UNC. Thanks a lot!
  8. So, those are the only two schools I got into. University of Maryland SPH, and Milken Institute SPH (GWU). Milken is significantly more expensive (about double UMD) but doable w/ loans if I work part time. I'm fine with both of the actual programs themselves in terms of courses offered, but is either one held in significantly higher regard than the other? Will the school's reputation matter much for an MPH in Biostatistics anyway? I talked to a couple of advisors but didn't get any definite answers.
  9. I was wondering how much weight does having a decent GRE Math Subject Test has on an application. If so, what should the target range be for domestic/international students?
  10. I recently received admission offers from U of Michigan's MS in Biostatistics program and Purdue's Statistics program, and I'm having trouble deciding between the two! I plan to pursue a Ph.D. after graduation. Both programs have pros and cons, and it is tough to reach a decision. For example, the U of Michigan's Ph.D. in Biostatistics highly prefer their own MS students and has a higher ranking. While Purdue allows MS students, who wish to transfer to the Ph.D. program take the qualifying exams. I don't have a clear research interest yet. Will an MS or Ph.D. in Biostatistics narrow my choice in the future? I'm leaning towards Purdue since I am more interested in working in IT industry. Thanks in advance for any suggestions!
  11. I'm trying to decide between M.S. Biostatistics at Columbia and M.S. Applied Biostatistics at Boston U. The appealing thing about Boston U is that the program is only one year, as opposed to two at Columbia. Anyone familiar with the program at Boston U and if it would be better to tough it out for the extra year at Columbia for the benefit in the long run? Thanks!
  12. Touch Chicken

    UTHealth at Houston 2018

    Hi all, I am going to UTHealth for PhD in biostatistics this fall. Is anyone going for the admitted student day on April 6? Never been to Houston before, hopefully, it will be a fun trip.
  13. Does anyone know about biostatistic programs in Canada and how they are viewed in the academic/research field? Specifically McGill/uoft/waterloo. From what I have found McGill - some good professors (highly cited/good journals). Students are competitive in top PhD programs like Harvard/UNC/UW/JH . DLSPH- The school itself is at top public health school in the world. The statistics department at u of t is highly regarded as well. I do not know a lot about the biostatistics program, however, seems very applied. Waterloo - Heard this program is the best in terms of training (though not necessarily global reputation). People who work in the field have told me that Waterloo graduates are highly skilled.
  14. I received offers from the Dalla Lana School of Public Health at U of T, Waterloo and Mcgill for their MSc Biostatistics programs. There does not appear to be much information out there on biostatistic programs in Canada. Does anyone have any insight on the pros and cons of these three programs? How are they viewed in the biostatistics field? I am not completely decided on a a PhD yet.
  15. I'm fortunate to have been accepted to both programs. Based solely on research faculty and rankings, which is stronger? I can't find much information regarding the biostats program. Is it clumped together with the bio, med, or stats dept? In addition, if I'm looking for industry work which would look stronger? If you have any info regarding internal PhD conversion rates or on whether Duke's program has been on the up and up please let me know!!
  16. There are a few other current PhD students who frequent this forum. I've visited it on and off over the years, but I have not seen many posts from current PhD students about their experiences. I thought this may be of interest to potential applicants, so I decided to write about what I have learned (I am about to graduate, finishing my final defense and thesis in May). I am happy to report that my PhD experience was largely positive. 1) A PhD program is fundamentally a research degree, and research is nothing like taking classes. I think some Stat/Biostatistics programs do a great job of involving students in research early on through rotations with different professors or through reading courses to familiarize students with statistical literature. But there are a lot of programs where students do not start research until the end of their second year. And I have seen many PhD students who were very, very bright (acing all their classes, 4.0 GPA, etc.) but who really struggled with transitioning from being a student to becoming a researcher. I definitely think you should work hard in your classes so you can pass your written qualifying exams and so you can developed a solid foundational understanding, but once you get to the research stage of the program, you really do have to teach yourself a whole new area. Moreover, research is about discovering something new and pushing the boundary of your field. There is just no way of knowing if some "open problems" can be solved or not! It's not like solving a problem on a homework set where there is generally one correct solution/approach. If you do a theoretical topic for your dissertation, you need to prove new theorems that have never been established before, not just "show” something that already has a known solution. And even if you start working on a problem, you may get stuck for long periods of time (or need to cut your losses and give up), or you may end up somewhere completely different from where you started. Unlike problem sets and exams, there are no concrete solutions. For example, for the first paper that I wrote, I was stuck on a proof for my main theorem for three whole months. Nothing I tried seemed to work! But my PhD advisor pushed me to keep trying, and eventually I found the technique that worked. Phew! 2) A lot of the learning in grad school happens outside the classroom, and you need to ask questions. This comes from talking with your peers, meeting with your advisor, attending departmental seminars, and reading papers. Here is the thing: when most people start research, they do not yet have the skills to really excel at it. A small number of people are able to excel right from the get-go, but for most people, it takes a bit of adjustment, and that's okay! It is important to reach out for help if you need it. If I didn't understand an author's proof or a new concept that I had never encountered before, I would ask my advisor to help me. I didn't have much experience with high-performance computing or running simulations on multiprocessing systems, so I asked my more experienced classmates to help show me how to navigate it. 3) Everybody thinks about quitting at some point. This is perfectly normal. A PhD can be a very demoralizing, frustrating experience. Plus, things can happen in your personal life that can derail you. It's just part of life. When I felt like quitting, I just took some time off... maybe 2-4 days of not doing any work to recuperate and assess why I was putting myself through the PhD. After some time off (not too much time off), I could reason to myself why I wanted to get a PhD, and I got right back to work. So if this happens to you, accept your feelings, take a breather, and then really question your own motivations for pursuing a PhD. If you can answer this question to yourself, "Why do I want a PhD? Am I willing to 'tough' it out when I'm feeling frustrated?", then you will be able to pick up right where you left off. 4) Just about EVERYBODY gets their papers rejected, even Distinguished Professors and Nobel Prize winners. My PhD advisor has co-authored over 250 papers and is quite smart, and he still has papers rejected. Professors at all levels get their papers rejected, some multiple times before they are finally published. It’s part of the process. It also happened to me for the first paper I ever submitted. Rejection always stings, but I say if it happens, take a deep breath and cool off a bit. Once you’ve acknowledged the disappointment and cooled off, read the referee reports and comments from the Associate Editor very carefully. Peer review is inherently a subjective process, but for the most part, paper referees take their jobs very seriously, and there will be valid concerns and comments for improving your manuscript (even if some might not be the most diplomatic when letting you know the faults they find with it!). It may be that the journal you submitted to just might not be the most appropriate venue for your work. Or there may be more substantive changes that are needed to make your manuscript more acceptable for publication. After my first paper was rejected, I spent a lot of time with my advisor revising it. We eventually re-worked the whole paper (e.g. cutting down the length of the literature review to the most essential points), we proved a new lemma and a new theorem that showed our new estimator’s improvement over previous estimators, and we performed several new simulation studies that showed quite interesting results. We just resubmitted this paper, making appropriate changes suggested by the peer reviewers who had rejected the manuscript, and I have to say my paper was way better than before. The paper was better off in the long-run. 5) The choice of PhD advisor is critical. It's very important that your PhD advisor is someone whom you can have a great working relationship with, whose research is interesting to you personally, and who is actively publishing in respectable journals. I think the last two are more important than anything else, especially for academic jobs. You basically need to have quality papers and excellent recommendation letters if you want to get a good postdoc or faculty position. Some PhD students are hesitant to work with Assistant Professors and are "star-struck" but there's really no point working with a world-renowned professor if their mentorship style and their research does not align with your personal working style/interests. Plus, an Assistant Professor who is actively publishing their work in top journals can still help you develop your career. Some people need a bit more guidance and an advisor who gently “pushes” them, while others can operate fairly independently and do not need to meet their advisor very frequently. The working style of you and your advisor should mesh well if you hope to be productive. 6) The fields of statistics and biostatistics change very rapidly, so it's more important that you do research that "comes from the heart" than try to keep up with a "hot area." I would not recommend researching a topic that is so archaic and obscure that only a tiny number of people in the world are still working on it. But I also think that you should prioritize your personal interests above what's currently "hot." It can be very difficult to predict what will be "hot" years from now. For example, Dirichlet processes were not very popular when the concept was first introduced, but decades later, Bayesian nonparametrics have exploded in the field of machine learning. It used to be that SVMs were very popular and neural networks lost some of their popularity, but currently, it is the opposite. There is an explosion of interest in neural networks/deep learning and not as much in SVM. The fields of statistics and biostatistics are constantly evolving and changing, so trying to "time" your thesis to a "hot area" can be tricky. But most importantly, a PhD is a very time-consuming commitment (at least 2 years of research). So you do not want to be miserable the whole time you are doing it. So make sure to pick a thesis topic that you find interesting. You probably won’t be able to do that yourself at first, but to that end, your advisor will help you hone in on some interesting open problems to work on. Do not do a topic that you have no personal interest in! Sure, some people might be more impressed if you do (what they perceive to be) a more "difficult" topic, but at the end of the day, you're the one who has to live with yourself and your career choices. And if your heart just isn't into it, it will make finishing the PhD much more excruciating. 7) Do not assume that your PhD thesis topic is the only thing you will work on for the rest of your career. To tie in with my previous point, you can always change gears and switch to a “hot” research area after you are done with your PhD. Finishing the PhD is the start of your career and certainly not where you want to peak. A PhD dissertation is usually on a specific, narrow topic or set of topics. Some people are lucky and can milk their research area for the rest of their career, but many people aren't that lucky. Even if you want to go into industry, an employer of PhD graduates is going to expect that you can teach yourself new things (new software, new models, etc.) on the fly, even if you've never seen/used these things before. In fact, it is this creativity and ability to learn new things quickly that makes hiring a PhD graduate more appealing than hiring someone with juts a Masters. Likewise in academia, professors are teaching themselves new things and moving into new areas all the time. My own PhD advisor began his career doing frequentist nonparametric statistics, but now he has research in a variety of areas of Bayesian statistics. The postdocs I am currently considering are in entirely new areas that I haven't learned before. By the end of the PhD, you should ideally have enough maturity and initiative to teach yourself different areas of statistics.
  17. Hello! I am very stuck between Michigan and Emory right now. I know Michigan has a better biostatistics program than Emory. But in terms of location, I like Atlanta way better than Ann Arbor. In addition, I think the coursework (and the Qual) at Michigan might also be much harder than Emory. My plan after graduation is to find a job (Pharma/Tech/Consulting), so will there be a huge difference between these two programs? I know PhD students at Emory can find an outside intern job during the summer. I'm not sure if I could do the same at Michigan. Any comments are very welcomed, like the pros and cons for each of them? Thanks! I appreciate that very much.
  18. Has anyone received offers from Canadian MSc programs in Biostatistics?
  19. I have heard a few people claim casually that Harvard’s biostatistics PhD program is very “applied.” Could anyone elaborate what this might mean or whether this is in fact a general consensus about the program?
  20. DJ3Sigma

    Where to apply?

    Hello world, I would like some help in determining where I should be applying to for PhD programs? Although I applied this year, many of the schools that I applied to I know now were "reaches." So if worst comes to worst and I do not get accepted into any of my schools or do not receive enough funding to attend any of those schools I would like to know what my options are and where I should be looking for next application cycle? I have put some of my stats below. Undergrad Institution: Large public university Majors: Statistics (B.S.) and Physics (B.S.) Minors: Actuarial Science GPA: 3.30 cumulative, 3.30 major Graduate Institution: Large public university Major: Statistics (M.S.) GPA: 3.74 Type of Student: Male, Hispanic, Domestic GRE General Test: 156V, 161Q, 4.0AW Programs Applying: PhD in Statistics (will apply), PhD in Biostatistics (may apply) Interests: Machine Learning, AI, Big Data Analysis Research Experience: 1.5 years in Physics lab programming equipment (undergraduate volunteer). 1 year in Statistics group programming in C++, and R with research into causality in a Bayesian world (graduate assistant). I may have a publication by the end of the semester. Employment: Have worked as GA during my graduate studies in a center that focuses on biostatistics and performs statistical consultations for the entire university. Consulted on many projects. Skills: R, C++
  21. Hello, I would like some insight on the difference of a 1 year program vs 2 year program. I am interested in pursuing a PhD after my master degree. However, I am not 100% sure. Which is why I am interested in pursuing a masters first. However, would it hurt my chances of getting into a good PhD program later if I choose a 3 semesters master program at a higher ranked school vs a 2 year master program at a lower ranked school? I know people have said that 2 year program typically have more theory classes than 1 year classes. However, when I've been looking at the courses for each individual program (1 year vs 2 year), they do not seem to differ by much. But, do PhD schools weigh the difference more heavily? I'm hoping someone with some experience will be able to help me as I am in the process of making my decision. Thank you.
  22. Hi everyone, I am really fortunate and have received two offers so far. One from UW Biostatistics, and the other from CMU Statistics. Even if I receive no other offers, I'll have a really hard time deciding on a program. I'm not exactly sure what I'd like to do for research, but I've been generally interested in high-dimensional statistics, statistical computing, nonparametrics, statistical genetics, causal inference, epidemiology, and a few other rather niche areas. My ultimate goal would be to obtain a faculty position, but if that market tightens by the time I graduate, I'd also be very happy to work in industry. Also, I don't think this will be an issue in either department, but I really want to be in a friendly environment that is more collaborative than competitive. I know that UW Biostatistics ranks ahead of CMU and has a great track record of placing graduates in academia. However, I feel like CMU is a slightly better (i.e. near-perfect) research fit. I hope to visit both campuses but I just thought I'd seek out advice from you knowledgeable folk first.
  23. Hello, I am an international student but currently staying in the USA. I pursued my Masters Program here in USA. I am in the process of applying for a PhD program in Statistics or BioStatistics. Undergrad Institution: International University (Outside USA) Major(s): Economics and Mathematics GPA: 3.57 Grad Institution: US University Major(s): Mathematics GPA: 3.8 GRE General Test: Q: 157 V: 139 W: 3.5 Program Applying: PhD in Biostatistics or Statistics Research Experience: None Awards/Honors/Recognitions: TA Assistantship for Master's Program Courses at Grad Level: Partial Differential Equations (A), Abstract Algebra (A), Advanced Differential Equations (A), Combinatorics and Graph Theory (B), Theory of Statistics (A), Introduction to Numerical Analysis (A), Analysis I&II (A-), Applied Statistics (A), Statistical Computing (B+), Discrete Modeling and Optimization (A), Actuarial Science (A), Complex Analysis (A-), Experimental Design (A), Assistant : Teaching Assistant for two years Letters of Recommendation: -Assistant Professor in Statistics (Strong) -Professor in Applied Mathematics (Strong) -Associate Professor in Mathematics (Strong) I am aware that my GRE score isn't the best and I have no research experience (but let's overlook that). I am interested in universities based in Atlanta Georgia. Based on my profile, what are my chances of getting admission into the following universities? I need your suggestions and advice. Thank you. Schools: University of Georgia (PhD in Statistics) Georgia State University (PhD in Biostatistics) Augusta University (PhD in Biostatistics)
  24. I recently received admission offer from U of Minneasota and Boston U. Both are MS in Biostatistics program. I plan to go for a job after graduation. Both programs having pros and cons and it is really hard to reach a decision. For example, the program in Boston U is only one year, and it is surrounded by so many pharmaceutical companies which suggests more job opportunities. While U of M has a higher ranking, and it is highly possible to obtain financial funding support in the second year of study. Also my family is in Minneapolis, so I can live at home and save housing expenses if I attend U of M. Does anyone familiar with these two universities? Any suggestions? Thank you.
  25. I entered my MPH program as a Community Health concentration (or its equivalent). However, now I'm having doubts about sticking with it because I'm afraid that it's not as marketable as other concentrations (ex. Epi/Biostats). I was considering switching into Epi/Biostats, but community health is a little more interesting in me (though I do appreciate aspects of Epi/Biostats). Has anyone else been in a similar situation and can offer some advice?

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