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Computational Neuroscience Programs


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Hello,

 

I am looking for information on program rankings and admitted applicant profiles for computational neuroscience programs. These programs are much more math heavy than traditional neuroscience so I thought you folk might have some info.

 

GRE Scores?

Math/Physics GRE beneficial?

Weighting of undergrad/grad math coursework?

Is neuro coursework needed, or is neuro research sufficient?

What does it take to get into MIT? UW Seattle? Caltech? etc... 

 

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 one of my rec writers is based in the Stats department ,  gets his grad students from CS, EE, Neuroscience, and Stats, but is a  pretty big name in computational/statistical neuroscience. I chatted a lot with his students.  They seem to be closer on the science/engineering side of admissions. They expect you to have pretty foundational mathematical background like Analysis, Advanced Linear Algebra etc.. but don't really put that much weight on more crazy math. Research from what I gather is pretty important, like you should have at least one strong rec writer from computational neuro/neuroscience who knows your research potential. Neuroscience coursework seems to be pretty optional.

Edited by trynagetby
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1 hour ago, Scrappyhappy said:

Hi! are you applying to specific computational neuroscience programs?  I didn't think that MIT and UW had specific Ph.D. programs in computational neuroscience.  Usually, students base themselves in a home department, and conduct interdisciplinary research or join a specific training grant within the overall program.

^^ The reason I say this is because the admission requirements (or desires) will depend heavily on which home department you decide to base yourself in.  I can give some advice on neuro and math programs, but the requirements, I think, will be quite different between the two.  Do you know which department you'd apply to?

Edited by Scrappyhappy
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Oh I see. I’m definitely leaning towards applied math programs. I value the interdisciplinary possibilities and quantitative side much more than the particular specialization in neuroscience, although neuro is probably my primary area of interest outside of math itself.

I made another post in this forum about applied math programs after realizing that I would probably want to do computational neuro from a math program. That post has more info on my background and profile.

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Ah okay! From my knowledge, it seems that math programs will care much more about test scores/gpa/solid math background, and less about the specifics of your research background.  I can't speak to too many programs, but UC Davis, UNC Chapel Hill,  and UW seem like they have classic programs that people with interest in mathematical biology apply to.  Specifically, I think that NYU would be a great fit for your interests in computational neuro, and I can try to answer some questions about the environment/requirements there if you have any questions!  The math department has tons of faculty with various applied math research interests.

Edited by Scrappyhappy
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Thank you! In that case, I'll ask away.

In general, I'm definitely curious about the student-advisor relationship in such a multidisciplinary program-- is it common to have both a math advisor and a neuro advisor? How independent would I be at a program like NYU's? Most of my knowledge is about economics programs, which seem to generally allow students substantial freedom in devising research topics. My understanding of Neuro however is that your research is usually wholly dependent on the lab/advisor matchup. My preferences certainly lean towards independence, but I am wary of embarking on a lone journey at the the intersection of two fields I am not exactly an expert in, although I guess my expertise would lie in the intersection after-all. What is the culture at NYU in terms of publication expectations during the program? Do you know how their placements are? One of my concerns with going this route, although it seems unbelievably fulfilling and satisfyingly, is that I really have no idea what the job market or academic placement outcomes are like.

At NYU, is it a single specialization in a field other than math, or do they encourage a wider spread? I have only just started considering this stuff so please lay it on me if you have any insights or experiences that you think are relevant. 

I'm not sure you've seen my profile, but I am concerned about my cumulative GPA from my first 3 years of undergrad. Given that I have 3 strong letters, do you think I even stand a chance at a program like NYU? I imagine the math GRE could help me some if I do well?

 

Edit: I should add that my GRE sub-scores could definitely come up if that matters. I scored 168Q/164V/4.5W but this was on the low end of my practice tests. 

Edited by Cophysneurec
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You could definitely be jointly advised!  Math programs are also very independent, and I find that most of the advisors are pretty flexible at NYU math, though it depends on your professor at the end of the day.  You are correct that research in Neuro departments is more dependent on the lab matchup, but I think that also holds more for experimental students.  I think computational students are offered a bit more flexibility, just because in general, they tend to have multiple "advisors", whether they are based in Math or Neuro, because it is interdisciplinary and you need experimental/mathematical/computational viewpoints.  A bigger difference between math and neuro, though, is that the math department has funding for the students for 5 years, and many students use that funding for the five years, as sometimes their advisors cannot fund them.  In Neuro, they expect your advisor to fund you once you choose a lab (thought there is departmental funding if needed).  This could be why the research in Neuro departments is more dependent on the lab matchup. I think this funding cultural difference is because most neuro profs have their own grants, whereas not all the math profs do.  The departmental funding keeps people in the less NSF/DOD/ etc. funded disciplines.

You won't be alone if you are at the intersection of two fields, you will just need to be more proactive in forging connections between professors where there may not already be any.  Though, there are plenty of existing collaborations should you choose to go that route.

I am not sure about any publication requirement/expectation.  Math is highly variable, with applied mathematicians having more publications typically.  I would expect 2-3 by the end of graduation, from what I've seen from people on the more applied side.  Again, this is very field dependent; i.e. machine learning may have more

I'm not sure about the placements -- a lot of people do leave to go to industry but many go on to get postdocs! I would look at the faculty that you are interested in and see what their students did afterwards.  Across most programs, there isn't a "general placement" statistic that is informative to look at: e.g. at great programs, you could have professors that drive all of their students out of science.  It is more useful to look at these stats on a prof by prof basis.  That said, academia is competitive, regardless of what program you start in.  I would suggest not to worry about it too much at this stage.  If you decide to go the academic route, I feel that the postdoc will be more important for positions.

I don't think there are formal further specializations at NYU's math.  It's more where your research takes you. You could decide to do very varied work, or stick to one niche.  It is up to you!

your GPA is going to hurt, but your post bacc will help! Math GRE will be very important.  A good score and statement may help offset the GPA.  You could also reach out to profs you are interested in, and have a chat with them, maybe they'll put in a good word if they really want you as a student.  I can't say that you have great chances, but with hypercompetitive programs, it's hard to tell about anyone.  All we really know is that you have to apply to get in!  No harm done by trying.  

For your applications, I would try not to solely focus on computational neuro for the statement.  If you know that is your interest, I think a neuro program would serve you better! But if you have varied interests in economics, neuro, genetics, etc.  and a particular approach that you like that connects all of these fields, that would be a good reason to be in a math program!

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1 hour ago, Scrappyhappy said:

 

For your applications, I would try not to solely focus on computational neuro for the statement.  If you know that is your interest, I think a neuro program would serve you better! But if you have varied interests in economics, neuro, genetics, etc.  and a particular approach that you like that connects all of these fields, that would be a good reason to be in a math program!

This is exactly what I'm thinking at the moment. I'm digging the math more than anything and not super set on any one specialization. In that case, I will start studying for the GREm, and I may very well end up applying to both econ and applied math programs next fall. Thank you so much for your insight!

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  • 3 weeks later...
On 11/19/2020 at 3:47 PM, Cophysneurec said:

Oh I see. I’m definitely leaning towards applied math programs. I value the interdisciplinary possibilities and quantitative side much more than the particular specialization in neuroscience, although neuro is probably my primary area of interest outside of math itself.

I made another post in this forum about applied math programs after realizing that I would probably want to do computational neuro from a math program. That post has more info on my background and profile.

I know both the applied math and neuroscience programs at UW well. It's always UW because they don't want to be confused with WashU. The applied math and neuro programs have very different approaches to who they choose and both are extremely selective so I'd be very careful. The applied math programs looks for A's in upper-division math courses like intro to analysis or abstract algebra and also that you took graduate level courses and did well. The neuroscience program is like any top neuro program in that they highly value grades but especially research experience and good LoR's. 

UW is highly highly interdisciplinary when it comes to applied math and neuro: it seems like almost half the AMATH faculty there are affiliated with neuroscience. Big names here are Eric Shea-Brown, Raj Rao, Bing Brunton, J. Nathan Kutz, and Adrienne Fairhall among many others. They also have a comp neuro training grant and very active collaborations with the Allen Institute for Brain Science which is every theoreticians dream given the amount of high-quality data they produce.

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