Cophysneurec
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Posts posted by Cophysneurec
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Economics PhD? Admissions committees care much more about mathematical preparation than the economics, though you would probably need to take intermediate micro and macro if you haven't already. Theory is competitive but highly mathematical and draws on areas such as analysis, topology, graph theory, algebraic topology and even gauge theory.
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Hello, I am coming from a math background with experience in clinical neuroscience research (human EEG) and behavioral psychology. From what I understand, many PhD students specializing in mathematical methods for neuroscience are not required to actually work with animals directly, perform transections, etc... I imagine this depends on the supervisor and their lab. Is there any way of identifying programs where students on the math side are usually not expected to do lab work? Is this wishful thinking on my part, and should I expect to have to get my hands dirty at some point if I aim for a PhD in Neuroscience?
If you have any insight into that aspect of any of these programs, I would be especially grateful:
CMU PNC
Duke
UC Irvine
UCSB
U Washington
Caltech CNS
UCSD
Princeton
Cornell
U Arizona
Brown
Thank you.
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What I've discovered is that if you want good application advice you need to get really specific. Nobody has the time to vomit all their knowledge at you, so you have to ask specific questions about specific programs or particular aspects of your profile. Do your own research and then ask for input on the details you couldn't work out yourself.
-fellow applicant
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About how competitive is the Caltech Computation and Neural Systems PhD program? It ranks with UC Davis in the US News rankings, is it similarly competitive, or is it more elite than the ranking suggests?
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23 hours ago, statsguy said:
I would probably not mention it. Say something along the lines of "despite struggling to find my way in my first two years of college, I overcame adversity and realized I need to take a different approach. This is why I did far better in the second half, despite having a tougher workload." Obviously you'll need to wordsmith this and make it sound polished and convincing, but you get the drift."
This will help me get past my block. Thank you.
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On 8/8/2021 at 10:27 PM, bayessays said:
Other people may have different opinions on this, but I would also be worried about it being judged negatively, and the people on admissions committees are just humans like us, so I would leave it off.
It would be another story if you didn't have a long history of improvement. But lots of people screw up at the beginning of college. Do you have some research experience and some close relationships with professors to write you letters? These will also help.
I had Bs in calculus and a B- in linear algebra first year of college and it didn't present huge obstacles for me in stats PhD admissions.
I will follow your advice, this is really reassuring. Thank you.
Fortunately I do have good research experience and close relationships with a few of my letter writers.
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I will be applying to comp neuro PhD programs this fall. My academic performance in undergrad was strongly affected by untreated and undiagnosed ADHD and resulting anxiety. It was so bad that I earned a 2.96 gpa in my first two years, and after seeking treatment I earned a 3.64 gpa in my last two years of undergrad. I have gone on to do the equivalent of a postbacc, with much more rigorous courses than I took in undergrad, and I've earned 3.9+ gpa.
Unfortunately I took the entire calculus sequence and ochem during those first two years (C's and B's), and was told by a professor at a program I plan on applying to that I will need to explain the circumstances leading to my poor early grades. I am worried that the stigma around ADHD may do more harm than good if I am honest in my SOP. Should I actually mention ADHD at all? Should I say I had anxiety due to life circumstances or something instead? Would ADHD actually be a diversity bonus, and help my profile??
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I will be applying to mathematics PhD programs this fall. My academic performance in undergrad was strongly affected by untreated and undiagnosed ADHD and resulting anxiety. It was so bad that I earned a 2.96 gpa in my first two years, and after seeking treatment I earned a 3.64 gpa in my last two years of undergrad. I have gone on to do the equivalent of a postbacc, with much more rigorous courses than I took in undergrad, and I've earned 3.9+ gpa. As I continue to catch up developmentally with my peers who had a lifetime to build study habits, rather than a measly few years, the ease with which I earn high marks is rapidly increasing.
Unfortunately I took the entire calculus sequence during those first two years (C's and B's), and was told by a professor at a program I plan on applying to that I will need to explain the circumstances leading to my poor early grades. I am worried that the stigma around ADHD may do more harm than good if I am honest in my SOP. Should I actually mention ADHD at all? Should I say I had anxiety due to life circumstances or something instead? Would ADHD actually be a diversity bonus, and help my profile??
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Wow, you weren't kidding! I really appreciate your input, so thank you.
How did you go about contacting/networking with PI's when you were applying?
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Hello, I am interested in Neuroscience programs, particularly computational ones such as UCSB DYNS. Please let me know what schools would be in a reasonable range for me! My undergrad started off very poorly but I have been turning things around.
Type of Student: White Male
Undergrad Institution: Top 3 UC.
Major: Economics
GPA: 3.4 Overall, 3.77 after Sophomore year (including Post-bacc)Key Courses by Year:
1st-- Calc 1 (B-), Calc 2 (B), Calc 3 (C), PChem1/2 (C+/B), Cells&Tissues (C-)
2nd-- Calc 4 (C-), OChem1 (C)
3rd-- OChem2 (B)
4th-- Linear Algebra (B+), Differential Equations (A-), Stem Cell Biology (A-), Cell&Molecular Bio (A), Genes&Evo&Ecology (A)Post-bacc:
Math-- Real Analysis (A), Graduate Topology 1 (A), Graduate Real Analysis 1/2 (A/A+), Extremal Combinatorics and Graph Theory (A+), Proof Based Linear Algebra (A), Abstract Algebra 1/2 (A/A)
Other-- Electricity and Magnetism (A), Systems and Signals (A), Introduction to Control Systems (A), Neuroanatomy and Physiology (A), Neural Mechanisms Controlling Movement (A)
Programming: Used Python professionally and in neuro research + numerous Coursera certifications. Used Matlab for engineering courses (Systems and Signals, Intro to Control Systems).
GRE Q/V/W: 168/164/4.5
Programs Applying: Neuro/Computational Neuro
Research Experience:
- 14 months neuroscience research (EEG data analysis) with solid writing sample to show for it, extensive programming, data analysis and literature reviews.
- 12 months grant apps and research in behavioral psychology and neuroscience with professor at high-ranking program with 2 coauthors on behavioral psychology papers.
Work Experience: Close to 1 year work experience as Analyst where I did ARMA forecasting, market research and data automation for a startup.
Letters of Recommendation:
- Professor of Graduate Real Analysis 1/2. Class of 7 students and I was at the top every quiz/test. Participated actively in class and prof got to know me fairly well, and saw me interact extensively with peers.
- Psychology Professor with whom I did 12 months research. Know each other personally, and spoke on zoom for 1 hour every weekday as he was paying me to help with research.
- Head of neuroscience lab, lecturer and MD at undergrad program. I know for a fact that this letter is very strong.
Research interests: Networks and complex dynamics, conscious access, brain-machine interfaces, brain disorders (e.g. Parkinson's)
School List:
- JHU
- Columbia (Neurobiology and Behavior)
- UCSD (Neuro -> Computational Neuroscience)
- UCB
- University of Washington
- University of Pittsburgh (Neuro -> Computational Neuroscience)
- USC
- UCSB (DYNS)
I am still working on finishing up the post-bacc, so some grades above are hypothetical, although things are looking great so far. I plan on applying to programs this year.
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8 hours ago, stemstudent12345 said:
Hmmm, I agree that there definitely needs to be changes in how things are run well before the post-graduate level (see my earlier comment about conservative economist Glenn Loury and redirecting energy toward correcting key developmental inequalities early in life). However, at the risk of overanalyzing, I think it's interesting that you use the words "burden" and "disruptions" to describe basic inclusivity efforts. I 100% agree that faculty are doing invaluable work on research and that should be their priority. However, having diverse communities makes research better for everyone (even in fields where it's not traditionally valued, like STEM fields). (I haven't actually read it yet, but this article has been on my list for a while and may or may not support my point). Even if I didn't believe that everyone deserved the opportunity to at least work hard and pursue their interests as far as they were able, I would at least recognize the utilitarian value in not discounting huge amounts of natural talent and potential for hard work among people who happen to belong to certain racial/gender/etc categories.
I wasn’t describing equity programs as a burden, I was referring to the effects that these institutionalized changes have on those who must enact them on a daily basis. Just as there is no free lunch, every policy has its downsides, whether in opportunity cost or in direct consequences of the policy.
I don’t appreciate the implication in your last point that I somehow don’t feel everyone should have the opportunity to pursue their dreams. I think this is the single most important facet of society. My thought is that homogeneity of any kind is not inherently valuable. Seeking homogeneity in the distribution of people who do a given thing is idiotic without basis for value. You don’t need to lecture me on the value of X Y Z in stem; what I am asking is: in what way does the undergraduate educational system or surrounding structure inhibit those who would naturally want to enter STEM from doing so? I feel that from my own experiences, these effects are very limited when it comes to women. I am asking for other perspectives so I can broaden my understanding.
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4 hours ago, stemstudent12345 said:
Your story actually gives me a good idea -- perhaps the department could offer funding for a summer review course before the program for those who need it.
This sounds like a great idea. Economics programs hold a ‘math camp’ during the summer before the first year, and I have heard it can be invaluable.
I have another thought on this issue, and I want to preface it by saying that creating opportunities for disadvantaged individuals to pursue higher education, elite careers, or what have you, is extremely important and valuable for everybody over the long term. My thought is basically just this: how much of this burden should fall on universities and their faculty? It seems like preferential admission of disadvantaged people can be a source of hope of opportunity and possibility for the younger generations (particularly helping those who would feel forsaken by birth or by consequence of some event), and those who succeed in the system can later become role models who guide those facing similar difficulties.
I wonder though if creating disruptions at the frontier of research is really the best way to do things. My feeling has been for some time that we need to ramp up free, quality education at the k-12 level with free clubs and activities for all students, better systems to identify gifted students, free daycare programs so that teenagers are not expected to care for younger siblings, free associate degrees and perhaps more. I understand that women tend to face difficulties with differences of communication styles when in majority male environments. Maybe I am blind, but I have not noticed any discrimination towards women in math or science among my peers. It seems to me there is a certain stigma around becoming an engineer or mathematician that evokes a very nerdy numbers obsessed and un-feminine stereotype. But is this stereotype just a function of the subject matter? Is it pernicious in some way? I feel that these career paths also tend to turn off the most masculine men who would not mesh with this stereotype either. I keep hearing about data in Norway showing greater behavioral divides between the genders resulting from greater gender equality, and I really wonder if women face exogenous (others discriminating against them) difficulties with higher math/engineering, or if many women happen to have personalities that don’t always mesh so well with the lifestyle of a math geek or engineering nerd. Sorry for rambling, I’m not trying to impose my view on anyone, but I’m hoping for your thoughts and feedback as my perspective is of course limited.
I would just like to add that I think there’s a good chance that women tend to be slightly more gifted in stem areas (based on higher overall college and especially k12 achievement). And I think it would be wonderful for the scientific community of there were more women involved. But even with that, the proportion of women in the medical fields is very high as far as I know.
To the poster above, please consider the validity of that test. Aside from that, interventions based on such a test have been shown to have net zero or net negative effects. It seems like bunk science to me. Maybe a better measure is needed.
http://www.hcdi.net/reliability-and-validity-of-implicit-association-test/ -
1 hour ago, TroyBarnes said:
1) Admit any one who wants to attend based on a college entrance exam (kind of how its done in some foreign countries)
2) In specified periodic time intervals, there are qualifying exams to be taken. Those that fail below a certain cutoff will have to leave the school (analogous to PhD exams)
3) Those that can finish all the coursework and pass all the exams are able to graduate (schools graduate too few/too many students a year should be audited for quality of education)So you're proposing "a college entrance exam (kind of how its done in some foreign countries)" (point 1). And then you said "Nowhere did I suggest people should be evaluated on such exams," referring to timed, closed problems, on strict standards.
So logically, your entrance exams would be untimed, or consist of open problems, or not be standardized. And these exams would be like those in some foreign countries, so supposedly there are countries that operate like this (not just at one program, but some country's programs operate like this). What countries do this?
Then presumably students would have to take standardized qualifying exams (point 2), because if they are not standardized across programs your (point 3) is entirely nonsensical. So these routine qualifying exams would be untimed, or consist of open problems (based on your own response, since they would be standardized). If your audits do nothing, no program would comply. So you would need to punish them for poor performance by your metrics. How? Funding? How is funding determined when all programs are expected to perform above the same threshold? Do government grants then take into account the compliance rating of a given program? Ok, but this doesn't work. The tests are untimed, remember? So the program can simply instruct students on the exam material during the exam... Or if not, the exams consist of open problems, which makes no sense (timed exams where students are expected to solve open problems in order to stay in the program??). How do you even construct fair exams containing open problems that are standardized by field and timed??
And schools would be audited for low graduation rates by some overarching body (point 3) so you are advocating for centralized control of the graduate educational system. So many issues with this. Who decides what areas of research in a given field are worth evaluating? These questions are hard enough at the K-12 level.
QuoteOne method for examination is in grant writing/fundraising, which should be a key skill of a researcher. In one of the programs in bioengineering, their qualifying exam consisted of writing a grant proposal in a simulated environment over a semester. The students were then evaluated on how well they were able to convey their ideas, and some could not proceed with the program. This would be one example of a potential "exam."
[...]
Further, rec letters, GRE, and GPA are one of the biggest factors in admissions already [...] By your logic, do you suggest to remove all metrics based on testing?How do you evaluate students on "grant writing" in a standardized way across institutions? If you do not standardize this process, what incentivizes programs to invite audits upon themselves due to low graduation rates? What is comparative advantage?
Exam is a very misleading term as you are using it. Perhaps evaluation would be more appropriate?
rec letters: based on ability to get along well with superiors and peers, grades, testing, research experience.
GPA: based on aptitude, consistency of work ethic, testing, and whatever else.
Of the three you listed, two reveal much more about an individual than how they perform on tests. My logic never indicated that testing should not be considered in the evaluation of an applicant or progress assessment of a graduate student. I simply pointed out that test scores alone can fail to capture many important facts regarding someone's research potential.
So far you write like a flopping fish, this way and that, with no clear direction, although any which way you flop you are confined to a space with no practical arguments as Mao Zedong smiles upon you.
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On 2/15/2021 at 11:41 AM, TroyBarnes said:
Here's a hot take on how I think academic institutions SHOULD operate in an IDEAL world.
1) Admit any one who wants to attend based on a college entrance exam (kind of how its done in some foreign countries)
2) In specified periodic time intervals, there are qualifying exams to be taken. Those that fail below a certain cutoff will have to leave the school (analogous to PhD exams)
3) Those that can finish all the coursework and pass all the exams are able to graduate (schools graduate too few/too many students a year should be audited for quality of education)So you believe that test-taking ability is the only important indicator of research potential? Did you know that many people with learning disabilities, adhd, or anxiety disorders tend to systematically underperform on tests, regardless of their intelligence, creativity (actually more creative individuals may very well perform worse in a testing environment, all else equal) or research potential? It seems you’ve only thought about yourself in writing this, which is uncharacteristic of a good researcher.
- TroyBarnes, stemstudent12345 and bob loblaw
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Why are you recommending Kent state in all of your comments?
- MLE and csheehan10
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Hello, I am interested in Applied Math PhD programs. I would almost certainly specialize in computational biology to study mathematical neuroscience. Do I have any chances of getting into the schools I list? What other programs should I look into applying to?
Type of Student: White Male
Undergrad Institution: Top 2 UC. Post-bacc at combination of top-100/30/20.
Major: Economics
GPA: 3.4 Overall, 3.60 in Economics, 3.85 last 100 credits (senior year and post-bacc)
Math Courses:1st-- Calc 1 (B-), Calc 2 (B), Calc 3 (C)
2nd-- Calc 4 (C-)
3rd-- None
4th+-- Linear Algebra (B+), Differential Equations (A-)Post-bacc: Real Analysis (A), Graduate Topology 1 (A+), Graduate Real Analysis 1/2/3 (A+/A/A), Extremal Combinatorics and Graph Theory (A), Mathematical Modeling (A), Abstract Linear Algebra (A), Electrodynamics Optics and Relativity (A), Probability Theory 1(A), Abstract Algebra 1 (A), Optimization (A), Introduction to Networks (A)
Programming: Python (1 yr professional + neuro research/coursework), R, Stata, Excel.
GRE Q/V/W: 168/164/4.5
GREm: not taken, will take next year.
Programs Applying: Applied Math PhD (computational neuroscience or economics/dynamic systems)
Research Experience: over 1 yr neuro research at excellent lab with solid writing sample to show for it, extensive programming, data analysis and literature reviews. About 1 year with business school professor at high-ranking program with 2 coauthors on behavioral psychology papers.
Work Experience: Close to 1 year work experience as Analyst where I did ARMA forecasting, market research and data automation for a startup.
Letters of Recommendation: One rec from Graduate Real Analysis 1/2, one rec from business school professor, one rec from head of neuroscience lab.
Research interests: Computational neuroscience, networks and complex dynamics, graph theory, optimal control theory
School List (so far):
- UC Boulder
- UC Davis
- Ohio State University
- UCSD
- UW
- USC
Concerns: Calculus grades, overall gpa.
Let's just say I did not have it together in early undergrad...
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Hey Casiorti, it sounds like you are very familiar with applied math programs and their admissions standards. Would you mind taking a look at my profile?
I would really appreciate any input you might have.
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Hello, I am interested in Neuroscience programs, particularly computational (I am also considering applied math PhD to study the same topics). Please let me know what schools would be in a reasonable range for me! I have no idea where I could get in as my undergrad started off very poorly due to a number of personal reasons, but I have been turning things around.
Type of Student: White Male
Undergrad Institution: Top 3 UC. Post-bacc at combination of top-100/20.
Major: Economics
GPA: 3.4 Overall, 3.60 in Economics, 3.85 last 100 credits (senior year and post-bacc)Key Courses:
1st-- Calc 1 (B-), Calc 2 (B), Calc 3 (C), PChem1/2 (C+/B), Cells&Tissues (C-)
2nd-- Calc 4 (C-), OChem1 (C)
3rd-- OChem2 (B)
4th+-- Linear Algebra (B+), Differential Equations (A-), Stem Cell Biology (A-), Cell&Molecular Bio (A), Genes&Evo&Ecology (A)Post-bacc: Real Analysis (A), Graduate Topology 1 (A), Graduate Real Analysis 1/2/3 (A/A/A), Extremal Combinatorics and Graph Theory (A), Differential Geometry 1/2 (A/A), Numerical Analysis 1/2/3 (A/A/A)
Programming: Used Python professionally and in neuro research + numerous Coursera certifications, R, Stata, Excel.
GRE Q/V/W: 168/164/4.5
Programs Applying: Neuro/Computational Neuro/Decision Science (any recommendations here are welcome, I am most interested in the quantitative side although I do appreciate the brain in its entirety!)
Research Experience: over 1 yr neuro research (EEG data analysis) at excellent lab with solid writing sample to show for it, extensive programming, data analysis and literature reviews. About 1 year with psychology professor at high-ranking program with 2 coauthors on behavioral psychology papers, also assisted with 7-figure grant submissions.
Work Experience: Close to 1 year work experience as Analyst where I did ARMA forecasting, market research and data automation for a startup.
Letters of Recommendation: One rec from Graduate Real Analysis 1/2, one rec from business school professor, one rec from head of neuroscience lab (absolutely stellar recommendation).
Research interests: Computational neuroscience, networks and complex dynamics; conscious access, graphical representations of neurons.
School List:
plz help!
I am still working on finishing up the post-bacc, so some grades above are hypothetical, although things are looking good so far. I plan on applying to programs next year.
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Bump! Any suggestions for what programs my profile is competitive for?
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On 12/8/2020 at 11:43 AM, tokingphd said:
Hello, I am math and statistics major and I was considering applying to a couple economics PhD programs in addition to statistics ones. Does anyone have more insight about the difference in job opportunities for the two fields? I know it is likely to overlap a little.
I have barely taken any economics courses but I assume my math and stats coursework is helpful
Econometrics
Mathematical Statistics 1,2,grad
Calc 1-3, diff eq, lin alg
RegressionI have 2 more semesters before I apply to anything, what sort of classes are economics phd programs looking for?
Job prospects are probably a bit better in economics, salary wise and availability wise, in academia especially. The federal reserve employs many economists, others work in think tanks on policy issues, the elite work on decision theory, and many more are in academia working on topics in macroeconomics or applied microeconomics. Real Analysis would help your application substantially, as would intermediate microeconomics (usually second course in micro).
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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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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.
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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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Hello, I am interested in Applied Math PhD programs. I would almost certainly specialize in computational neuroscience or economics/dynamic systems. Please let me know what schools would be in a reasonable range for me.
Type of Student: White Male
Undergrad Institution: Top 3 UC. Post-bacc at combination of top-100/30/20.
Major: Economics
GPA: 3.4 Overall, 3.60 in Economics, 3.85 last 100 credits (senior year and post-bacc)
Math Courses:1st-- Calc 1 (B-), Calc 2 (B), Calc 3 (C)
2nd-- Calc 4 (C-)
3rd-- None
4th+-- Linear Algebra (B+), Differential Equations (A-)Post-bacc: Real Analysis (A), Graduate Topology 1 (A+), Graduate Real Analysis 1/2/3 (A+/A/A), Abstract Linear Algebra (A), Graph Theory and Networks (A), Differential Geometry 1 (A), Optimization (A), Mathematical Game Theory (A)
Programming: Used Python professionally and in neuro research + numerous Coursera certifications, R, Stata, Excel.
GRE Q/V/W: 168/164/4.5
GREm: not taken, will take next year.
Programs Applying: Applied Math PhD (computational neuroscience or economics/dynamic systems)
Research Experience: over 1 yr neuro research at excellent lab with solid writing sample to show for it, extensive programming, data analysis and literature reviews. About 1 year with business school professor at high-ranking program with 2 coauthors on behavioral psychology papers.
Work Experience: Close to 1 year work experience as Analyst where I did ARMA forecasting, market research and data automation for a startup.
Letters of Recommendation: One rec from Graduate Real Analysis 1/2, one rec from business school professor, one rec from head of neuroscience lab.
Research interests: Computational neuroscience, networks and complex dynamics, economics (decision theory, macro).
School List:
- plz help!
Relative number of applicants by program type?
in Mathematics and Statistics
Posted · Edited by Cophysneurec
added (PhD)
Title.
It might be helpful to me and others if people with insider info shared a rough ratio of this years applicants to previous years. Personally I am trying to decide how much energy to put into planning profile-enhancing activities in 2022 should I get rejected everywhere. My field is math/applied math (PhD), but I think hearing about biostatistics or other quantitative programs would still be helpful.