F30 for math-type research

[tortuga87]

I'm in the grad school phase and would like to apply for an F30 soon. I work in the bioinformatics and biostatistics realm, in terms of developing new math theory and computational methods. I notice that things tend to move more quickly and differently than my colleagues who have to wait for cultures/animals. So... I have three problems that may be unique:

1) I usually have an idea and end up exploring it intensely for 2 or 3 months until solving it. So, by the time I finish writing an F30, the problem is already solved and doesn't seem worth writing a grant about.

2) Nine out of ten of the ideas that I come up with are junk (1 only works). So, general ideas behind a grant can be easily thrown out the next day, if it is doesnt work.

3) I take many more classes than usual, >15 classes in total. I have been told that this weakens the F30 application, because people see it as taking time away from research. However, in the quantitative sciences, pretty much everyone takes a heavier course-load and its generally necessary in order to do the cool stuff.

So I am always stuck with new ideas that are completed without a grant and find myself paralyzed when it actually comes to writing an F30. I feel like I just end up writing about esoteric junk that I find out doesn't even work midway all the while in a class situation that's considered disadvantageous

Has anyone encountered a similar situation or can recommend some strategies?

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[mercaptovizadeh]

I would either give up on applying and just crank out papers and try to get out in <3 years.

Or, if you really want a grant, set up a meeting with a computational biologist or biostatistician or what have you and ask how they write their grants, i.e. the major themes, overarching concepts, etc.

You probably just have to "meta-ize" your ideas, i.e. abstractify them, generalize them, and increase the scope of what you're proposing so that it covers years of work rather than months. Think of it being analogous to bench scientists proposing to do 10-15 experiments rather than just 2-3 experiments.

 

[gutonc]

1) I usually have an idea and end up exploring it intensely for 2 or 3 months until solving it. So, by the time I finish writing an F30, the problem is already solved and doesn't seem worth writing a grant about.

So I am always stuck with new ideas that are completed without a grant and find myself paralyzed when it actually comes to writing an F30. I feel like I just end up writing about esoteric junk that I find out doesn't even work midway all the while in a class situation that's considered disadvantageous

Has anyone encountered a similar situation or can recommend some strategies?

I just want to point out that this is the grantwriting process, in pretty much all of science, in a nutshell.

The typical 3 aim grant is structured like this:
Aim 1: Something I've done and written the manuscript for, just waiting to get this grant out before I submit it in case the grant reviewer is also the manuscript reviewer.
Aim 2: Something else I've already done all the experiments for. Just working on the M&M section and figures right now, the rest of the manuscript is done. This will be submitted right around the time the grant award letters come out.
Aim 3: A bunch of stuff we've started doing already...should be done by the time the year 2 money is being disbursed.

2) Nine out of ten of the ideas that I come up with are junk (1 only works). So, general ideas behind a grant can be easily thrown out the next day, if it is doesnt work.

10% of your ideas are good/work? Then you're doing pretty well for yourself. Hopefully by the time you make full professor it will be up to 25%, but don't expect much more than that.

Honestly, the only real issue you have is the large volume of coursework you have. That and, like mercaptovizadeh said, you need to "embiggen" your proposal. You need to think of each of your "ideas" as parts of a single aim.

 

[tortuga87]

I just want to point out that this is the grantwriting process, in pretty much all of science, in a nutshell.

The typical 3 aim grant is structured like this:
Aim 1: Something I've done and written the manuscript for, just waiting to get this grant out before I submit it in case the grant reviewer is also the manuscript reviewer.
Aim 2: Something else I've already done all the experiments for. Just working on the M&M section and figures right now, the rest of the manuscript is done. This will be submitted right around the time the grant award letters come out.
Aim 3: A bunch of stuff we've started doing already...should be done by the time the year 2 money is being disbursed.

Thank you, those three aims helps me make more sense out of it. I was reading some past F30s of my bench colleagues, and they seemed very specific about doing X, Y, and Z. Now I get it's because they figured most of it out already

 

[radiology2014]

I agree with the above advice, especially regarding broadening your aims in general.

I also came from a quantitative background, but luckily was not saddled by lots of mandatory coursework. I followed some early advice I was given to pick a grad department with the most flexible (easiest) requirements and then design my own perfect curriculum. I echo this advice to other MSTP students, since timeline is critically important, and it is much easier to add interesting/unique courses than it is to get out of mandatory requirements. Since you're already in this track, though, I would at least try to spin your rigorous coursework as a positive under the "training" component of your grant.

For my F30, aim 1 was statistical methods development, aim 2 was an application/collaboration in the neurosciences, and aim 3 was another application/collaboration in clinical neurology/psychiatry. The methods development and associated paper were already written when I applied, and the collaborations were already established with strong letters/evidence of support and preliminary data. The F30 was very well received and funded easily.

 

[Neuronix]

1) I usually have an idea and end up exploring it intensely for 2 or 3 months until solving it. So, by the time I finish writing an F30, the problem is already solved and doesn't seem worth writing a grant about.

If it's a good question/problem, give some of your preliminary data and pretend it hasn't been solved yet.

2) Nine out of ten of the ideas that I come up with are junk (1 only works). So, general ideas behind a grant can be easily thrown out the next day, if it is doesnt work.

This is why you need preliminary data.

3) I take many more classes than usual, >15 classes in total. I have been told that this weakens the F30 application, because people see it as taking time away from research. However, in the quantitative sciences, pretty much everyone takes a heavier course-load and its generally necessary in order to do the cool stuff.

Yuck. Coursework in grad school generally helps little and prolongs the PhD. I try to steer people doing quant stuff to departments that don't have a lot of requirements so you can take exactly what you need quickly and move on with our ridiculously long training.

Has anyone encountered a similar situation or can recommend some strategies?

Find a lab and piggy-back onto your mentor's ideas. This whole thread should be something taken care of by good mentoring, i.e. your PI.