Azazel

Do you have a friend who's already in a PhD program? Maybe they'd be interested in collaborating on something. This would work even better if you're super friendly with a professor. Otherwise, maybe reach out to some professors who would remember you from undergrad, and see what they say?

1. Thirding all the other people who said, "no." 2. I don't think so. You can play this in a bunch of different ways. Personally, I pretended like I wanted to stay in the area where I'd build up a research track record, then I switched areas once I was accepted to grad school. That made it easier to tell a story in my applications. That's not the only way to do it though --- I know people who were more straightforward about switching in their applications, and they were still admitted to top schools.

I'd second most of this advice. Letters of recommendation are the most important thing. Sure, publications are really helpful, but if you have really strong letters of recommendation written by people known to the admissions committee, it won't matter too much either way. Incidentally, the Stanford CS PhD admissions committee doesn't even read your SOP --- don't know how that compares with other schools.

Here are two examples of successful personal statements which, to varying degrees, address this question: Jean Yang's (now at MIT) and Ethan Fast's (now at Stanford). From Yang's (for CMU, where she got in): My career goal is to remain in academia as a professor so that I can pursue my research interests while training and recruiting others to solve relevant problems in programming languages. I want to continue my studies at Carnegie Mellon because it has a large programming languages group with many professors with whom I would like to work, including Professors Harper and Aldrich. Because I find it important to talk to with different areas of focus than my own, I also like the diversity of CMU's computer science research. Because I look forward to teaching as a graduate student, I like that CMU has a reputation for having motivated undergraduates who can challenge my understanding of the materials. For these reasons, I would like to spend my next six years at Carnegie Mellon. From Fast's: My research explores the boundaries of automated software development, investigating to what extent computers can assist humans in writing code. In particular, I am concerned with how techniques from machine learning might be applied to applications in programming languages. Along these lines, I am especially interested in working with Professor Engler on automatic bug detection, Professor Aiken on statistical debugging techniques, or Professor Koller on applications of machine learning. By combining statistical learning methods with elements of semantic and program analyses, I hope to construct algorithms that reduce the cost of developing reliable code. [And later, addressing fit:] In working with Professors Weimer and Forrest, I have learned much about what it means to produce high quality research, and I have come to realize that I will need a PhD to work on the cutting-edge problems with which I am interested. Moreover, I expect that I would thrive at Stanford. My contributions to APR occurred at many levels of the research process, from high-level brainstorming and hypothesis formation, to the logistics of experimental design and academic writing. Further, I have published work contributing directly to the state of knowledge in programming languages and machine learning. In short, I have discovered a passion for that deep level of understanding enabled uniquely by research, and as a graduate student at Stanford, I would have the resources and mentorship necessary to pursue this passion fully. So I actually don't think you need to be particularly convincing (neither of these examples were!)

You have the right idea; if your time is limited, don't re-take the GRE. Research is far more important. Focus on getting good research experience and letters of recommendation, and those things will maximize your chances at top schools. If the admissions committee sees a wonderful LOR from someone they trust, no one will care about GRE scores.

If you want an industry job as a software engineer, I don't think it matters. Write good code (and pass interviews) and companies will be happy to hire you. No one will care much about your research (e.g. all those PhDs who go to google don't work in their former research area). If you want an industry research position, then of course it matters more. The key question here is: does your research have an industrial application? I'm pretty sure some companies hire all sorts of researchers (e.g. you can probably work in almost anything at MSR) but in general I don't know the ratios. A priori, HCI or networks would seem a safer bet. You have other options, too. You could become chief scientist at some smaller technical startup, or a data scientist ("big data" is popular), CTO, etc. These positions often require a scientific background and credentials (and networking!), but in most cases your research isn't directly relevant. So I'd say do what you're interested in if you can get it funded. You'll probably do better work. And unless you have very specific career goals, I wouldn't worry too much about a job.

Between the two, I'd say Computer Science; it's the safe, standard bet. But you might rethink getting a degree at all. It's surprisingly easy (and much less expensive) to teach yourself programming (or even the CS theory behind it) if all you want is a job in industry. Programming jobs tend to be meritocratic, and I know plenty of people who hire candidates with no formal CS background. You just have to signal that you're good (e.g. contribute to open source, write a technical blog, post personal projects online). Then pass the interview... A degree will help, but it doesn't signal all that much, relative to what you've actually done/built. Also, many people get their jobs through networking. So teaching yourself while developing a network (attending events/conferences/hackathons) might be a better use of your time. Here are a few other options I can vouch for (again, if all you want is a job): https://www.hackerschool.com/ http://www.bloc.io/ Doing a CS degree can be rewarding, but it's not the only way to enter the industry. It's also pretty expensive.

If you're really not sure what you're interested in, I'd consider a few things: - How interesting do you find the general faculty at each school? (e.g. which school is better if you want to switch advisors) - Which advisor is most (or at all) amenable to "letting" you switch, if that's what you want? While no advisor can stop you outright, some can probably make it painful. (Sounds like UCSD has the edge here). - Which advisor is most open to interdisciplinary collaborations? (e.g. what anacron mentioned) Do they expect you to come in and work on a big project, or are they open to something new? You can try to figure this out via email, if you're careful. - What are common student outcomes for each advisor? How well are students placed, and how well are they doing? Depending on your answers to these questions, it may be better to reapply, although UCLA and UCSD are both good schools. If you reapply, will you be getting any new (e.g. better) letters of recommendation this time around? Rec letters are often the determining factor, especially at top schools. And I think the difference in prestige between UCLA and UCSD is pretty much a non-issue. While I've never lived in LA or San Diego, I'd probably lean toward San Diego (better weather, less traffic/sprawl, more laid back).

If something sounds boring, don't study it for your PhD And AI can be very practical. Just ask the ML people. I'd probably choose UCSD. But this should be a very personal decision, based primarily upon advisor fit. How well do you like the potential advisors at each school? How well does the research they do fit your interests?

I agree. I almost never suggest that anyone take the CS GRE, but OP sounds like exactly the sort of applicant who might benefit from doing so (assuming a good performance). Can you get in touch with your old CS professors? Letters of recommendation are the most important part of any PhD application. So if you want to get in to a good program, you should make your subgoal: "Get really good recs from one or two CS professors." Of couse achieving this isn't easy. Is there some way to leverage your background in law? If you can find a law-related area of CS research, some (good/well-known) professors might be interested in taking you on as an RA. You can work for them as long as it takes to get a good rec (a year, maybe). Even if you have no intention of continuing research in that area, it might be a good way to bootstrap an application. Your psychology research should also help a little bit, and you should try to get another letter from whoever you worked for. I don't think this sort of rec will greatly influence an admission committee, but it's still a great deal better than the "did well in class" recs that they see all the time. Some of what I've said seems to conflict with your current plan. In particular, I wouldn't tie myself down to any particular region by buying property. You might also consider increasing your ambitions. There's no reason you can't go to a school like MIT/Stanford if you play your cards right. For instance, if you can find an MIT prof who's interested in having a lawyer as an RA (which doesn't really sound so absurd), that rec letter can turn into gold... Hope this is somewhat useful.

You're right: MIT isn't a good example, but GREs don't matter (particularly at top schools). Just don't fail them. What you should worry about, in order of importance: recommendations, research experience, publications, grades, GRE. (This is possibly on an exponential scale.)

Yes. Although CS is gradually moving toward a more post-doc centric system, TT after grad school is still a fairly common career path. None of my advisors/mentors have done post-docs, and I don't get the impression that they expect me to do one either (speaking way too soon, but if I were to go into academia...).

I don't know how the singularity institute is viewed inside academia, but I would be hesitant to invest much time there, given to the lack of PhD researchers among their faculty: http://singinst.org/research/residentfaculty I'm sure the institute does good work (probably?), but graduate admissions committees typically want letters from people who hold a doctorate.

Maybe. But if you are working in computer science, it's not uncommon to get a tenure-track position straight out of grad school.

I agree with newms, although that UTEP admissions estimator is garbage. Want a good predictor? Ask professors where they think you will get in. And do research. It will give you a sense of whether you actually want to go to grad school (extra important for a PhD). Even better, it will likely get you some decent LOR, which are (IMO) the most important part of your application. If you find that you like research, and you want to optimize your grad school chances, you might even consider spending an extra year at undergrad. One year is often not enough to get anything interesting done, or to publish. On the grade issue: