I am currently starting my second year of PhD study in mathematics at an institution ranked 70-80 in math in the US. In my first year, I have taken some courses in probability theory and passed two of three qualifying exams.  After taking the probability courses and since my girlfriend is pursuing a master in statistics. I found myself really interested in statistics, is it wise to get another PhD in statistics after finishing PhD in math, or should I try to apply for a PhD in statistics now?   Is it possible for me to get admitted to an good institution(ranked 30-40 in US) with only some backgrounds in math?
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I am studying a combined bachelor of engineering (electrical) and bachelor of mathematics; I just started this year and will graduate in 2018. The reason why I am doing double degrees and not a single degree is because I love both electrical engineering and mathematics and I could not ignore any of them. So with this in mind, I am thinking of doing two PhDs when I graduate (one in electrical engineering and one in mathematics). Is this a good path or I should concentrate on only one of them?
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I recently read on stack overflow that getting two PhDs just shows that you're unfocused and you don't know what you want to do. However, I'm at a small school with a 5 year Computer Engineering bachelors/masters program I feel like I should take advantage of, but I'd also like to go on to do another part time grad degree in the same field or Computer Science at a larger, better established school, while I work.   If I went to a larger school like University of Illnois or MIT or similar, will having a masters and going back for another be frowned upon, or is this a non-issue?
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Background: Five years ago, I obtained a Master's Degree from a top 10 American university in the Social Sciences.  I was a novice in academia, only one year post completing my Bachelor's degree, and simply not yet ready for the rigors of professional academia.  I had virtually no quantitative background from my Bachelor's degree, but after my first semester during my Master's program, I became interested in quantitative analysis, and registered for a doctoral level course in quantitative analysis.  I was simply not able to keep up with the course, and I received a C-, and my performance in my two remaining classes for the semester was negatively affected, and I earned a B- and B+.  For my final semester, I got my act together and earned three solid A's, including in two very quantitatively oriented courses.  I went on to pursue a second master's degree in a foreign school where, although by no means as prestigious as the first, I had a 4.0 GPA.  However, I am quite confident that my low GPA of a 3.33 from the first Master's will immediately kill any chance I have of receiving an admissions from American schools, which essentially means that one poor performance five years, at a time when I was an entirely different individual, will forever preclude me from pursuing my life's dreams.  I do not believe that it is in any way immoral to want send the transcript of my second master's degree, which I feel better represents who I am and what I am capable of, though obviously I am well aware that this is not allowed.    I am not trying to avoid responsibility for my academic performance, I am simply looking to pursue my life without being kept back by one poor performance five years ago.    Questions   Is it possible to request from my first university to have my degree revoked and registration cancelled in a legal, open, and transparent manner?  Is there any way that I can, once again, legally and by the book, not be forced to send in a transcript which will assuredly destroy my chances of being accepted or looked upon as series student?
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I hesitate to ask this question, but I read a lot of the career advice from MathOverflow and math.stackexchange, and I couldn't find anything similar.   Four years after the PhD, I am pretty sure that I am going to leave academia soon. I do enjoy teaching and research, but the alpha-maleness, massive egos and pressure to publish are really unappealing to me, and I have never felt that I had the mathematical power to prove interesting results. However, I am really having trouble thinking of anything else to do. Most people seem to think that the main careers open to mathematicians are in banking and finance. I really want to work in some field where I can use mathematics, but it is also important to me to feel like I am contributing something positive or at least not actively doing harm. For this reason, financial speculation is very unappealing to me, although I do find the underlying mathematics quite fascinating.  Here is my question: what careers which make a positive contribution to society might be open to academic mathematicians who want to change careers?
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I'm a first-year graduate student working on probability and I am learning statistical inference by myself, I have skimmed  through a few books like Casella /Hoggs but I find they omitted lots of details, for example, they didn't introduce the conditional expectation, so there are only proofs in discrete case about "sufficient statistics "  "factoring theorem ", etc. could you recommend me a book for graduates or doctor degree that cover basic ideas of statistical inference and rigorous proofs? thanks!
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I am 33. I live in the US. I am a neither a US citizen, nor a green card holder. I have worked in various jobs as a research assistant (physics, biology, economics) usually involving programming, mathematics or statistics.  As a newly minted undergraduate, I didn't really have much confidence in myself and I completely ruled out graduate school as pointless.  I didn't think of myself as smart enough.  I drifted into working in labs, because those are some of the easiest ones for which one can get a work permit in the US as a non-American.  Having worked in academia for a while now, I've had a chance to leap into various fields and help build solutions to complex problems.  I think I have literally gone as far as I can go researching in academia with no higher degree.  I work at one of the top universities in the world.  (If you looked at US News rankings or the Academic Ranking of World Universities, it's in the top 5.)  Lately, I've been thinking about applying for graduate school.  I do have a few papers in various fields.  I'm thinking of a PhD in either pure mathematics, applied mathematics, statistics or computer science.   I see two big minuses to applying to graduate school:   Most people applying are more than a decade younger than I am.  (Alas, more than a few gray hairs have made an appearance in recent years.) Perhaps my achievements would look good for someone younger, but partially my achievements are the result of a long career rather than any special brilliance. So, I wonder how my record will be perceived.  I did take GRE and I scored 800 quantitative, 800 verbal and a 5 on the essay.  (I would most likely have to do a GRE subject test depending on what field I ultimately decided.)   Please advise on how accomplished, but older candidates, are viewed in the graduate school application process.
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I start my master studies this fall in quantitative finance/economics in Europe. Since this will just take 3-4 semesters I want to take a look ahead and obviously PhD is one option to do.   So I am wondering if it makes sense to go to the US for PhD, since I will have already a master's degree in two years. I read a lot about the US PhD's which can be started after bachelor and therefore are somehow like a European master &amp; PhD combined.   I saw some PhD programmes from well-known US universities and their curriculum contained almost just courses I will already have in my master. Wouldn't that be a waste of time to repeat them? Specially compared to my country (Switzerland) where a PhD duration is between 3-4 years.  Every input/personal experience will be appreciated.
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indicates that holders of a master’s degree are held to higher standards when it comes to graduate admissions. The stated requirements for some graduate programs () also outright exclude applicants with doctoral degrees. These seem to be saying that holding a higher degree prior to application is a disadvantage (a fatal one in the case of a PhD). This also applies to private universities: Stanford  (at least in computer science); .  I don't understand why:   If there are two applicants, Alice and Bob, who have achieved largely similar things, it seems logical that both should have a roughly equal chance of being admitted. However, based on JeffE's answer, if Alice has a Masters degree while Bob does not, it's Bob that gets admitted instead of Alice. JeffE's answer even indicates that if Alice has achieved slightly more than Bob, it's still Bob that gets admitted.  If graduate admissions is looking for students that are capable of succeeding in its program, then Alice should be more likely to succeed than Bob since she's already had some experience of graduate study. This should be even more the case if Alice already has a PhD – if she can do it once, she should be able to do it again.    JeffE's answer indicates that since Alice has had more opportunities than Bob, she should also be held to higher standard. However it should also be true that Alice has already achieved what Bob has yet to and in fact might not be able to achieve. Further, JeffE's answer seems to be saying that Alice should do the academic equivalent of financial engineering and pass her graduate-level courses &amp; thesis without getting a master’s degree even if she qualifies for it, which sounds silly.  As for applicants with PhD degrees, my first guess would be that this is because , and the university is acting in the applicant's best interests. However if this is the case, then this is effectively telling the applicant "I know what you want better than you do", which also sounds silly. UC Berkeley's requirements also seem to be saying that if someone with a CV worthy of a tenured position were to apply for a PhD student position, the university will say "no" even though it's clearly better in their best interests (in terms of research output) to say "yes".   Presumably I'm misunderstanding something because if this behavior were irrational, it would already have been changed. What am I missing?  EDIT: I wonder if things are different in programs where the student is involved in research directly without spending time on coursework?
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I plan to apply for PhD in Finance/Statistics next semester, and hence searched for potential supervisors.  An issue I have is that many interesting candidates are above age 60, and in Germany Professors retire at 65, such that a subsequent post-doc/habilitation would most likely require a different supervisor after PhD. One Professor just started his position at age 40, but so he has not many notable publications and I am unsure whether he might change university soon (he just changed it from another 4 years position).  Could someone advise me on the importance of age for selecting a PhD supervisor in context of a long-term future academic career?  The time for PhD would be 4-5 years, and PostDoc/Habilitation/AssociateProf usually again 4-6 years, with goal of potentially becoming Full Professor in Finance/Statistics.
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I'm an undergrad in Australia, and at this stage I want to go on to do further study in maths (or maybe physics/CS, still have a few years till then).  Should I do so, I imagine that I will want to complete a PhD overseas. Possibly at a university in the US or maybe Oxbridge in the UK.  In Australia, PhDs typically take 3 or 4 years, and I would be eligible to go straight into a PhD upon completion of my undergraduate degree (it is research focused and includes an honours year, see ).  But, much of what I have found for overseas institutions has been in the range of 5-7 years, or maybe a 3-4 year PhD with a few years doing a master's degree beforehand.  Does this indicate that the level of rigour and amount of work produced is significantly different for various PhD programs, or is it the case that some programs are more relaxed and simply spread the same amount of work over a longer period of time?
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The situation: You did your B.Sc. and M.Sc. in CS with focus on subfield X1 and are now pursuing a PhD in subfield X2. There is a Masters program in subfield X2 available where you do your PhD that offers courses that allow you to advance in this subfield (which is pretty new to you).  Does it make sense to get a second M.Sc. while pursuing a PhD if the courses of the Masters program will be beneficial to your PhD work? Subquestion: Do you think it is even feasible to do this based on your experience?  The geographic context is Europe/Germany so a PhD does not include course work. A Masters (at a university of applied sciences) takes 3 semesters full time with the possibility to double that time when doing it part time.
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I am a senior who is graduating in December with a Bachelor's Degree in Pure math. I would really love to apply to the PhD program. However, I have been really depressed because even though I have a good GPA (3.85), and I have gotten mostly A's in all of my math classes (I have taken math classes up to Topology, measure theory, and Algebra), I feel like this is not good enough since I have 8 W's [withdrawals--no grade given] on my transcript. The horrible part is that 6 of these W's are on math courses. All those W's occurred during my first year at my university. The second year up to now I haven't gotten any W's.  My question is: How horrible (by the Committee who selects candidates for the program) is a W seen on a transcript? Is there anything I can do about it?  I feel like I have a big hole on my transcript, and it has been chasing me throughout my undergrad years even though I managed to hide myself from this monster and continued to take a lot of math courses, earning A's (and two B's) in all of them.
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I currently work as an Aerospace Engineer for the Department of Defense for nearly 6 years now, and I have a PhD in Aerospace Engineering from a top-10 university in the United States. I am seriously thinking of doing a 2nd PhD in Computer Science, because I want to eventually own an Algorithmic Energy Trading Firm and need to become an expert in Machine Learning algorithms.  As of now, I am working on a few journal papers to publish and I am not going to have any problems getting strong letters of recommendation from my employer and professors on campus.  I ought to be able to get a letter from the Dean of my college as well.  So, I am thinking of a second PhD in Computer Science because I really want to immerse myself in Machine Learning and figured a PhD was the way to go.  Question for everyone:  Would it be a challenge for me to acquire entrance into a top 5 school in Computer Science for a PhD?  I ought to mention that my PhD research was in Computational Fluid Dynamics, Turbulent Flow and I had to develop my numerical solver and turbulence models in Object-Oriented C++.
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I'm applying for research-based Masters in Oceanography. So far, I've lined up advisors at University of Massachusetts (an intercampus program), South Florida, Georgia, and New Hampshire.  According to ,they are in top 150 globally for oceanography. Moreover, my current work supervisor says 3/4 are well-known.  I've also been talking to a UCSD prof. He told me he is unsure if he will be taking on students but is more inclined to accept a PhD student (since they'd be with him longer). I would really like to go to UCSD for my PhD.  Will going to a lower ranked MS have a big effect on PhD applications?  What can I do to distinguish myself in PhD application 1.5 or 2 years from now should the MS be low rank?
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According to Stanford's Computer Science graduate admissions department this year:     110 students were accepted. Nearly all accepted applicants were from Stanford (BS/MS), MIT, Berkeley, Princeton, Michigan, Texas, Washington, Tsinghua, and the other ivy leagues. About 10-20 were from non-top schools.   I am one of these 10-20. I go to a state college and our curriculum is imaginably not up to par with the elite schools.  I'm scared.  Did anyone experience the similar situation?  How would I prepare myself to hang with the smartest people in this Ph.D. process?  If you're a professor, how much does this affect you in choosing a Ph.D. student?
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I am starting a Master's conversion course (in Computing and IT Management) but I am still very unsure about all of the details about doing a PhD such as where and what I want to do it in. Some programs require that you have you Master's certificate to hand when applying too, and I haven't even started my MSc yet.  I was thinking of taking a gap year after the MSc to continue my entrepreneurial activities and goals, to find some temp/contractual work and to give myself more time to apply to PhD applications.  Would this be beneficial or detrimental to my applications and academic prospects?
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To give you some background, I have a grasp on the basics of statistics and probability theory and even remember touching Bayes theorem at the university data mining course. But being a few years away from the university made my math got extremely rusty (so much for last-minute pre-exam cramming). While I remember various random basic concepts, there are a lot of gaps in my understanding of them.  What would be a good material (a book, a site, or otherwise equally accessible medium) to revise the fundamentals and go beyond basics? I'd like a book that can be actually read as a book (most statistics books are really dry and are close to being reference material, rather than a book).