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good morning I think we'll go ahead and get started thanks a lot for spending here early part of your afternoon on a perfectly serviceable Friday with uh with me um so today we're going to be talking about a writing effective proposals for fellowships and grants and I'm gonna cover both fellowships and grants and there are a lot of similarities there are some differences too and I'll talk about those as we go along um my name those of you whom I haven't met I'm Darren lapomi I'm a professor in Nano and chemical engineering and also associate Dean for students in the Jacobs School of Engineering at UC San Diego all right so what are we going to talk about so what is a research proposal a research proposal is the vehicle by which you communicate with an audience your idea and why it should be funded is the importance of writing a compelling research proposal the reason that we write is because we can't plug into the reviewer's brain directly the writing process the process of making figures is this thing that takes a hundred hours to do when eventually we will hopefully just be able to make some kind of a neural link to the people and they will automatically appreciate why our ideas are the best and deserve funding unfortunately committees can't do that yet so you need to do this process of of writing using language and figures and so on one time I was at a grant writing Workshop put on by the NIH National Institutes of Health and one of the program managers said that there are many more bad proposals than bad project ideas and that good ideas get obscured behind bad pros and bad arguments the figures that can't be discerned to the extent to which that's true in the extent to which he was just trying to be nice to the audience of uh of NIH awardees I'm not sure I have my own opinions on that but I'll get to in a little bit so what are we talking about in terms of Grants versus Fellowship so graduate students how many are grad students in the audience how many post-docs okay so a grad Fellowship is more like judging you and your academic achievements and slightly a little bit less on the actual research proposal itself For Better or Worse at the postdoc level so those of you who are grad students will be going on into a postdoc or even if you're doing a company and you're applying for a grant like an sbir or sttr grants for for a small company small business Innovation researchers small type transfer something or other I forgot what is TTR stands for but you'll be doing this process as well and even if you work at a big company you will always there will always be reasons for you to write up your results for getting more resources so this is relevant whether you go into Academia or not at the postdoc level a research Fellowship is much more like a grant so take the NIH f-32 award which is a postdoc Fellowship that is basically a grant given to the university to which the post-doc applies but the pi of the fellowship is the postdoc and it is written exactly like a grant would be written a grant proposal although we can't plug directly into the brains of the reviewers or the program manager or the scientific review officer is a psychology experiment it's a psychology experiment you have to begin the process of writing a grant Proposal with faith the faith that that blank computer screen that blank document can be chiseled away with your writing in such a way to reveal a project proposal that can be funded and will be funded much like this is attributed to Michelangelo the uh famous Italian artist that before making a a sculpture like the David Statue or the PA test statue that he envisioned that this block of solid marble already had that sculpture in place all he needed to do was remove the unneeded bits you have to have faith with that blank piece of paper or blank document on your screen has a winning proposal in it what is the life cycle of a research proposal a research proposal one time I wouldn't necessarily recommend this Ascent that this be how you approach research proposals but one time I was for about 10 years of my life I was totally uncaffeinated and the reason is because in grad school I spilled acid on my face and I went to the emergency room for chemical burns and they told me that my blood pressure at Pulse were out of control because I was drinking like two pints of coffee every morning and uh then I did 23andMe and it said that I had to pour caffeine intolerance or even before for caffeine tolerance and uh and to reduce my caffeine intake and one day in 2014 it was the summer I was walking around here in the bare Courtyard out just right outside here and I uh and I got a fully caffeinated latte because I had no anxiety-inducing meetings on my schedule that day and I was so wired and I said what can I apply for so I saw the solicitation for the NIH director's new innovator award which is one of the few brands that an engineer can apply to without having preliminary data at least in the NIH portfolio and so I outlined the whole thing like totally on this latte trip and I was I actually it ended up being funded and that completely changed the trajectory of my career so I'm not saying that um you know let me begin a research proposal by uh by um you know consuming large amounts of caffeine although that may work for some people but a more reliable way to do it is to take notes at all times so always have a place to take notes I often take notes in terms of voice memos not voice memos that I've listened to but voice memos Voice to Text memos actually use the dictation app for that um called Dragon anywhere I compose emails to myself all the time wouldn't it be cool if you could uh you could use some kind of skin cream so that it was possible to feel light as tactile stimulus um so there are a lot of ways that you might want to want to do this but as early as possible in the Pro in the past in the process look at agencies so that's NSF NIH other countries and have different institutions like encirc in Canada and European research Council and so forth um different companies have research solicitations to like Samsung LG and reviewed for those before and list what has been funded if you can find out if it's a U.S based agency they'll have a like a map or a list of where all this stuff all the funding came from or where all the funding went and you can see if those project titles and abstracts match the flavor of what you are trying to do so I'm a big believer in the idea of marinating in an idea so to give you an example I get a lot of requests to review papers from journals and I know that I don't have time to do the review right now when I get the the invitation but I'll look at it I'll open up the paper and just kind of scan through it and even if I don't do even if I don't revisit it to write the referee report for another week or so I feel like that one initial period where I have taken that information in is actually useful in something in the back of my mind like churns away on it and then when you see it again you're not seeing it for the first time and you approach it in a different light creates buckets in your mind so as early as possible before you've made any figures before you decided what your preliminary data is going to be have the agency in mind like look at that list uh cross-reference it with your idea see how you might be able to tailor that idea to that particular program also use this time uh well in advance of submission or writing to socialize your idea with colleagues that is subjected to conversational pressure because you can get a lot of free Consulting from your lab mates from your pi and where you say I'm thinking about this and they'll say well did you consider this and this and this criticism and like no maybe I didn't maybe I I should alter my Approach in some way because when starting out but even now even after 11 years as a pi nine out of 10 of my ideas are crap and the goal is to reduce that that number um and you do that by getting the by internalizing the feedback of others because they will approach your idea from a different perspective and you want to be able to uh to narrow down what is a what is a robust idea where you can run good controls where you can you can know um you know what has been done in the literature already because that's what people that's what your colleagues are really good for too is knowing like no so-and-so did that already or so-and-so did that already you might want to see what the pitfalls are and don't get embarrassed by doing this people people like to have their brain picked about ideas also because also when you have your own brain picked by somebody else you like to be able to like show off a little bit and ask like those pointed questions like um are you did you know why why would somebody use that device or like this companies the company is doing this or this research lab is doing it already find a day or a week or you have a full few blocks of time to work on your ideas and carve them out like this is once we start getting in the proper in the writing preparation stage and my suggestion is once you have your idea notebook or your voice memos or your dictation or notes that you've taken from conversations write down everything just write down little phrases because sometimes a little phrase that you write down or that you think of can actually trigger a whole Avalanche of like it can trigger a whole paragraph or a whole session of the graph like how would I elaborate on this one particular idea I have for this proposal it's not necessary to write a complete outline at this point so a lot of times when I do section headings so my my advisor was uh was um was my advisor still alive still is a person um uh George Whitesides um who was known for microfluidics and self-assembly and stuff he would say outline everything write down your intro approach uh experimental design results and discussion conclusions and put in all the subheadings what I found though is that I started to write pros and then I'd have to make huge changes afterwards when I realized the details of the pros didn't match the outline that I came up with before so don't don't you don't have to do this quite yet sometimes we use the idea of outlining as sort of an excuse to avoid the hard work of actually forming our our arguments so go ahead and just write as fast as you can use any um it just and by fast I mean not just for the sake of fast but so that you don't forget stuff that you wanted to put in there don't worry about the way that sentences are crafted at the beginning it's fine if they're 50 words long and you use all kinds of jargon at the beginning that's fine you can refine it later this is also the time when you find collaborators to fill in holes maybe your Pi can help you fill in uh fill in holes like I need a computation expert I need a biome an informatician expert I need a mechanics expert I need a chemist I need human subjects uh person I need animal facilities who are you going to go to to have access to those resources and that's it and you need to ask these people early work on the figures with a clear draft text as a guide and then finalize your figures later then finalize the text and uh and at that point you're finalizing the figures now the second half of the life cycle of a research proposal is when it's out of your hands so you submit the research proposal and you have a beer or sparkling water and then you wait three four five six seven eight nine months for news because it takes forever for stuff to get reviewed um even though oddly when you review for one of these agencies they demand your stuff in three weeks um and then you often you don't have actual funding for up to a year um so what does the review process look like so the program manager is the scientific manager of that particular realm of Science in the agency to which you submit the program manager may or may not be the same person as the scientific review officer that is the person that handles the peer review process at NSF they are the same person at NIH they are different people and I'm sure there's a joke in there about like Law and Order um where the narrator says the in the grant review system the grants are judged by two equal but separate organizations and so there's this whole scientific Review Office office that organizes the study sections they're called this is all for NIH then they send those reviews back to the program manager that is in National Cancer Institute National Institute for General Medical Sciences National Institute for bioimaging and biomedical engineering what have you there are like you know 20 some institutes within NIH and then based on the scores the program makes uh makes a decision on funding who is on the Review Committee they are peers that ostensibly or that nominally are from your field or field of research of your proposal um they're called it's sometimes called in in ad hoc review meeting so or committee so an NSF usually these committees are formed and dissolved with every batch of proposals that comes in so the same people are not necessarily on it every time at NIH may be around half of the people serve a four-year term those are called Stand um standing members of the study section then there are temporary members of the study section that rotate in and out maybe they'll do one or two in a row and or maybe one a year or something like that and maybe one only ever in an NIH proposal you get to you get to recommend that a certain Institute look at your proposal like NCI National Cancer Institute and you can also suggest what study section read it like cellular and molecular Technologies or instrumentation and systems development thinking about ones that tend to apply to engineers they don't have to take your suggestion but it's it helps them to provide a suggestion okay you want to you want to think about writing to generate Champions on the uh on the panel so if you can speak to a couple of people speak to the to your peers on the on the committee then when the panel gets together in in most cases they will get together they generally don't get together if you apply to DOD funding um usually those are all done by by email um uh at NIH and NSF they're usually done with a discussion depending on the stage of the of the process and if you have um if you can convince a couple of people in a really strong way to convince the panel that this is a strong proposal then you can kind of Leverage their voice um now how do you do this in practice well you write a an effective proposal that doesn't at least doesn't offend anyone right talk more about that in a moment so even even so scores usually end up being averages so in the NSF system you have poor Fair good excellent or good very good excellent and usually it's kind of an average of those in NIH land uh what you do is you have three reviewers and then they review the proposals ahead of time um and then there they go into a room either on Zoom or in person where there are 20 some people in this room and only three and they review 100 proposals or 80 proposals the um the top half are discussed and the bottom half are dreaded get a dreaded ND or not discussed and then those 50 that are that remain the three people that actually read The Proposal are like the lawyers arguing the case for or against that proposal or a mediocre lead of with respect to their attitude on the proposal and then they convinced the rest of the uh the jury basically the rest of the study section and uh and in the end everyone votes with a number they provide a number one to nine one being the best nine being the worst then you take an average of that number you multiply it by 10 and that's the NIH score so score is of like 30 and below are good are you know really solid in general those will get funded in general in general um so it's almost like and if there's an expert in the room who did not read The Proposal but can ask questions to the reviewers who have become experts in those proposals they behave like the like the like the jury except the jury can ask questions okay so then the scientific evaluation a sense of the program manager who makes the final funding decision in NSF it's a very similar process except that the scientific review officer is if he's in the room at the time of the scientific review is the same person who makes the funding decision at NIH all that stuff gets written up and then sent to a person who is not in the room and they make the funding decision Department of Defense a lot of that process is behind a closed door it's hard to get an idea of what happens there I know from being part of the process that proposals are sent to out for peer review but the program manager has much more control over the content of their portfolio than if not nominally then in practice then do program managers in the other agencies next getting into the mind of the reviewer first of all you want to make sure that you're aligning The Proposal with the funders objectives the program manager in particular is the first and last person that needs to be convinced whether this is NSF or NIH or doe Department of energy or DOD I have to restrict it to um U.S agencies because those are the ones that I know the most about and that other countries have similar systems for when some of you will be applying to Grants in other countries reviewers generally have good intentions but all have biases they have biases based on their scientific training they have biases based on knowledge or lack of knowledge about your Institution they have biases because you may or may not have smiled at them once at a conference they have biases related to all kinds of uh of of other characteristics that uh that may or may not paint them in the best light none will be an expert in everything in your proposal you are the world's biggest expert in your proposal if someone else is a bigger expert in your proposal I would find another topic to write a proposal on all of them know something about statistics experimental design okay I'm gonna go back because that that could be uh that could be Mis misconstrued and I also don't entirely agree with it every time none will be an expert in everything in your proposal there will be aspects your proposal will be better if you can draw from some aspect of your training or experience that someone else reading it is not likely to have because they will see that as oh that's a new that's a new angle I think we could learn something about the system that we wouldn't be able to learn without that kind of expertise however even though not everyone is a topic expert all the reviewers will know something about statistics experimental design how the likelihood of success matches with the convincingness of the preliminary data however not all Grant mechanisms require preliminary data and if you have preliminary data and those that don't want it then your proposal will get desk projected so make sure you look at the programs of solicitation and see what constitutes preliminary data is it a figure is it something unpublished is it something published sometimes it's helpful to hedge and say don't call it preliminary data call it proof of concept work or you call it a foundational observations um don't don't give them reason to make it give them Reasonable Doubt criticism usually results from omission of facts not from factual errors you can be pretty sure that what you put on there what you write is going to be correct you don't I mean we're all here we're all PhD students or post-docs um or professors and we are really really at the very least trying not to be wrong about stuff that we say right so we're pretty sure that most of the stuff we say is factually correct and when it's when we don't know if it's factually correct that forms part of the hypothesis or why you're doing the research to begin with we want to see if this is if this is the mechanism for such and such or if such a such a device can be accomplished using this particular approach however when you're leaving stuff out that's when reviewers pass so you leave out the statistical analysis you leave out why you need this number of animals in your study why you need this many replicates statistics that's the like the that's the soft underbelly of many proposals um if the type of measurement you're proposing say it's x-ray photoelectron spectroscopy doesn't match doesn't give you the kind of information that you that you're saying that it will they'll pounce on on on that um because you've you've left out the experiment that you need to uh to prove your hypothesis for this kind of or say you you are writing you're doing some kind of computer vision task or something and there's some algorithm that some researcher has developed and you didn't know about it or worse you knew about it and didn't cite it um those kinds of omissions those are the the unforgivable ones where if you accumulate a couple of those errors forget about it but for the most part they will believe what you tell them first do you know harm this is what they teach doctors don't say anything don't write anything that could be construed as arrogant or combative like a massive hole in the literature is such and such or these other researchers failed to account for a blah blah blah because one of those other researchers might be reading your proposal or maybe that researcher smiled at the person at a conference reading or proposal anticipate the concerns that a reviewer might have have a section explicitly on pitfalls and alternative strategies and this isn't a suggestion if you don't have this you will get hammered by at least one of the reviewers you know why because reviewers have they're busy and they've banked these criticisms in their minds and it's a bit like one of those child's toys where you pull the string and the arrow goes around and it goes the land's on the cow and it goes the cow says oh and it's like you pull the chain on the reviewer and it goes the the pi did not include anything about biostatistics pull a chain there's no pitfalls section the pi and the co-pi are located more than 100 miles away from each other how do we know that they can get in contact so there are the same criticisms that are used over and over and over again make sure that you explicitly address any program specific criteria in NIH okay sorry I keep bringing it back to NIH I know because I'm talking in the bioengineering building but um there are the five major review criteria significance Innovation approach investigators and environment in NSF we call this uh the two primary criteria are intellectual Merit and broader impacts those are quite a bit less specific but same kind of idea make sure you use those those words strategies to make the proposal reader friendly we'll talk a little bit more about this in a moment but make sure that your writing is coherent and I don't mean that like you know when you're about to fall asleep and you say something that's incoherent or you think something that's incoherent I mean one section should logically follow into the next uh one paragraph goes into the next one sentence goes into the next anticipate questions and answer them as you go try to get into the mind of the reader how do you navigate multiple agencies and programs there are a lot of idiosyncrasies of programs so NSF the buzzword is transformative transformative potential of This research NSF can tend to be more high-risk higher reward um the money outside of a few directorates and programs is not really that high if you apply in biological sciences there tends to be more competitive with NIH but at the engineering directorate it's definitely not sorry uh NIH like I said it has or 20-ish institutes and program and and institutes and centers or ICS and then you also have this other structure of the scientific Review Office your the Department of Defense which some famous members are Air Force office of scientific research afosr office of Navy research onr my research office aaro and also you have the defensive Advanced research projects agency or DARPA which is Department of Defense but has a different funding structure it's very much Milestone driven and it's a lot of money but the the there are a lot of Milestones that have to be that have to be reached Department of energy has multiple offices like Solar Energy Technologies office cedo it also has like Basic Energy Sciences Bes and so on you also have the derpa equivalent in doe called the arpa E arpa energy there are a few different dichotomies that you have to navigate and these where you are on these one-dimensional Spectra will depend on what type of agency and program within that agency and even solicitation within that program bonding to so there's basic on one hand versus applied on the other there's low risk on one hand versus high risk on the other now no one ever brags about doing a low risk proposal right but the the r01 mechanism in NS in NIH which is the primary sort of the the lifeblood of nih-funded researchers those uh proposals have to have a high success rate like you have to have all your ducks in a row you have to be pretty sure that what you have is going to work based on your preliminary data right now they call it the rigor they change the word from preliminary data to rigor of previous results or something like that use the word rigor and then uh but then there's also like the transformative r01 transformative research award which is in the office of the director which is high risk and you don't include pulmonary data in that mechanism then you have incremental versus transformative similar to low risk versus high risk but not necessarily you could have a transformative idea that was also low risk what are some differences between agencies in terms of the application process so look at due dates even within one agency like National Science Foundation um engineering directorate a few years ago changed its policy where it didn't have specific dates it said it was rolling acceptance of proposals all year the catch is once you submit a proposal you have to wait another year before you can submit it again whereas in principle if your next due date came six months later for a different agency say DMR division of materials research and then then you had all your comments back and stuff then you could address them and resubmit it within the same year which isn't very likely because that would require a super fast turnaround um but it's in principle possible there are also some idiosyncrasies about when or if you should reach out to the program manager so I have historically always gotten this wrong when I was an assistant professor one time I went to the program program officer at NSF and I had already submitted a proposal but I was in Washington DC for another reason and I asked if I could meet and we had a nice discussion I asked um asked about various program priorities and so on and then the next day the program The Proposal I had submitted like a week earlier showed up in the guy's inbox and he called me on the phone and said this was was uh so dishonest of of you I thought I might have given you I would have been more guarded in what I said but the reason I didn't ask anything about the proposal I just asked about the program was be was because of that because I didn't because I didn't want to think well I already submitted it now there's nothing I can do right so I had a very general conversation the program manager was very upset about it it ruined totally ruined my day in another since working with a with somebody in another agency I won't say what it is because it would narrow them down way too much they said this is like three months before I submitted a before the due date for this particular proposal and the program manager said I can't meet with you when you come to Washington DC because you haven't submitted the proposal yet and I fear that I would give you an unfair advantage completely the opposite guidance so there is no uh so I guess what I could say is talk to the person a year ahead of time and then you'll be safe then you'll be safe in some cases a program manager will discourage you from submitting it to their program okay so you don't submit your proposal to their program because they they know how Pro how proposals tend to do on certain topics in their program but beware of cases where the program manager tries to tell you how your your proposal would be perceived in other programs one time I had a program manager who turned down a proposal and said that they shopped it around to a bunch of other programs and no one was willing to take it no one would no no one said that it would be a good fit for the program but I had already written it and I submitted it to another program anyway and it got funded not only did it get funded but it broke my long losing streak at uh at NSF of 11 proposals rejected in a row between 20 14 and 2019 so sometimes you have to take the information you get with a grand assault there will be eligibility criteria for different programs that you really really have to keep in keep in the back of your mind ink in the front end of your mind does your project involve humans if it involves humans is it merely human subject research or does it qualify as a clinical trial and what's the difference a clinical trial studies the effect of a proposed intervention intervention is the key word are there animals involved is your iacook protocol all set up yeah is there foreign involvement are you shipping samples to another country how do you find the right program solicitation well it's a it's a mess out there and I didn't uh I didn't learn this till very far into my my program and nobody told me what I'm telling you right now so within each agency there's something like a directorate then there's something like a division divisions within that directorate and then there's a program for example the agency might be NSF the directorate might be engineering the division might be C bet which is chemical biological environmental transport I don't know why those particularly get grouped together but there it is and then the program might be disability and Rehabilitation engineering sometimes programs are coded to correspond to different fields and you might not be aware of this the first time you look cmmi is um I'm totally going to get this wrong but uh manufacturing mechanical Innovation something like something like that it's basically where civil engineers and mechanical engineers send their their stuff now there's a biomechanics a mechanobiology program within cmmi and okay so there's some overlap with bioengineering that and some other fields C bet chemical and bioengineering environmental engineering transport phenomena anything that involves Heat heat and mass transport and you could go on and on eccs is the ECE I forgot what the one for uh for CSE is uh has a c in it for computers um what's important is that although you might look at that solicitation and say oh my idea fits into these words I could see how it could be construed but it can fit into those fields but the reviewers that those program managers select might not be in your field it might be quite far off it might furthermore be like offended than an outsider applied to their pot of money that's reserved for their field this is kind of like the hidden curriculum of obtaining funding so everyone's heard of NSF nihdo doe dood but then that's the tip of the iceberg there's all this other stuff under there venture outside your field at your own risk so you're if you want to apply for something outside of your field make sure your language your jargon is impeccable and they will hear that you don't have the same scientific accent that they have they'll say no that's not a an afferent that's a meccanosensory corpuscle or whatever like no that neuron doesn't terminate in the dorsal horn it terminates in the dorsal root ganglion okay those would be factual errors but you get the point there are other ways of speaking a language where you're not quite using the language the way a professional in that field would so if you go outside your area make sure that somebody who really knows goes through your language and they get make sure you're using it right how to address specific solicitation requirements in your proposal if they bothered to put it in the solicitation you have to address it so no clinical trials so if you do something that looks like an intervention it'll get desk projected coming up with novel ideas I guess this is like core of the whole thing right have all the good ideas been taken I personally don't think they have been uh how do you find new ideas I think the best ways to look between fields that don't often talk to each other so all my best collaborations right now are with so I'm a organic material scientist engineer organic material signs of the session here whatever um you can see I think a lot of the boundary between science and engineering anyway so my most profitable collaborations have been with psychologists neurobiologists Behavioral Sciences and the reason is if you can make an effort to speak their language a little bit and you can meet them halfway think about them as islands in the ocean and there's a big blue ocean in the middle between these areas of learning where there's all that knowledge to be created and the farther apart you are the more information the more knowledge there is to be created in the middle that's one one way another way is to look at the intersections of your interests so it's pretty improbable that any one of us is the best bioengineer the best structural engineer the best computer scientist the best mechanical engineer best chemical whatever but I would be willing to bet that every single person in this room is the best at some product of three or more capabilities what do I mean by that if I look at my skills as Kent as a chemist so my undergraduate degrees in chemistry so maybe I I like maybe I know maybe I'm in the top 10 of scientists that would know something about organic chemistry okay um burnishing my credentials a little bit too much maybe I'm maybe I'm in the top 30 um let's just say one in ten then I'm one in five at somebody that knows of somebody that knows something about uh mechanics so now I'm one in ten times one in five so I'm one in fifty now I'm starting to look pretty good now I'm one in two at somebody that knows something about psychology now I'm one in a hundred and what if I I'm not a computer scientist but what if I spent a lot of time as a kid like coding what if I have another factor of two in there I'm one in 200. and you start doing this and if you start combining finding a way to dovetail these disparate interests and experiences then by definition it doesn't take many of these skills to be the absolute best at something that occurs at the intersection between these skill sets how do you put the pieces of a puzzle together for a research proposal go to conferences even if you're not presenting even if there's no money in your Pi's budget it will repay the investment even if you just go I mean it sucks if your Pi is not going to pay but the or they don't have the money to pay but it is the premium that you will get on your your lifetime earnings potential by getting this in by having this experience working on these ideas earlier rather than later it's like compound interest like having a penny and doubling it every day for a month and at the end of the month you have a million dollars talk to a lot of people try to get sleep easier said than done taking walks right stuff down how to distinguish between incremental and transformative research ideas um same things as above talk to talk to colleagues talk to lab mates conversational pressure ask your colleagues for examples ask your classmates for examples ask your Pi for examples of funded research proposals oftentimes they'll give it to you I've I have a DropBox that I've shared with a bunch of people that has every version of funded proposal I'm going to post this video publicly and I'll probably get like 100 requests for share access to that Trump I just demonstrating the feasibility of innovative con Concepts we've talked about this kind of already and repeating myself a bit but sometimes feasibility is not really necessary in a high risk High reward how do you demonstrate your uniqueness why are you the right person for This research so take your experiences and kind of focus them in on this particular problem people will believe what you say but you have to think of examples so like I'm really good at math so show cite something that shows like how you model this or that you came up with some analytical or numerical solution to some problem showing a strong track record and relevant research that's that's key unless it's something that involves a pivot so the F32 for example a lot of you will be applying to an F32 like like thing that's the NIH postdoc Fellowship they want to see a pivot if your work is too close to what you already did it'll get Tamed and then basically talks about that already resources just show that the place you're preparing to go to or the place you are now has the resources like equipment how do you know how is the reviewer going to know that UCSD has an NMR no um letters evidence uh you know say what building it's in that makes it real in the person's mind usually there's a separate document for that so it doesn't count against your page limit ways to demonstrate your access to the necessary equipment especially if it's not on campus highlighting collaborations that have provided access to additional resources so publishing papers together with an international collaborator or a collaborator in Ohio or Pennsylvania or someplace far away from San Diego having a track record of publishing together is important right a few tips on writing clearly and concisely if you're interested I have stuff on my YouTube channel about this multiple hours of videos on how to write concisely and clearly um avoid excessive hedging so in most cases this will probably generally speaking and do this I think people will give you some leeway there academies academies is like really long sentences like sentences more than 20 words academies involves excessively long words like stick to three syllables or less I'm not kidding six to two or less where possible um got as opposed to receive oh wait only Siri okay um signposting so avoid like first I'm going to tell you this and I'm going to tell you this if you're writing is coherent enough it'll be obvious use short words and sentences jargon doesn't make you sound smart it makes the reader feel dumb avoid redundant information towards the logical flow of ideas and coherence so critically each paragraph has to start with a topic sentence that has the beginnings of an argument not just a title so chemical libraries are used often in screening for agonists for cell surface proteins okay that's a title it's a statement but if there's no torque in it there's no reason why somebody should consider should can continue reading that paragraph say something about combinatorial libraries and screening for small molecules each paragraph has to end with a sentence that begs the next one so set up a little bit of uncertainty unless it's the last oh no even if it is the last paragraph to be entire paper make the reader want to continue each sentence ends with the heaviest or most important information or the longest element of a list read The Proposal out loud if you get out of breath or not delighted by the exactitude of every sentence rewrite it because there is a lot of like cognitive mode involved in processing long sentences figures all proposal I'm running out of time so I'll go fast all proposals have to have figures a nice figure overview that ties everything together like a graphical abstract on the first page or as early as possible that gives you the whole idea of the whole fellowship or Grant proposal all at once is awesome start on the figures early use Simple color schemes like the Google colors um or use you know some other color scheme but be consistent the font size must be absurdly large in illustrator PowerPoint Etc so that it still looks good when it shrunk down to three inches crop out the native scale bars on a microscope use a sans-serif font because if you write it in all Times New Roman it looks like it was written in 1890. preparing a budget the budget may or may not be a scorable Criterion but the reviewers will see it it's a bit like in a courtroom how many of you have been on jury duty so sometimes in a courtroom the judge will say the jury will discount that statement because an objection has been sustained but the jury already heard it how could they completely reject it from their psychology the budget goes in whether it's a scorable Criterion or not so the reviewers see it and they see if this person is being greedy or there's no way that this instrument costs this amount of money Personnel or the most expensive part of the budget enter your own salary into the grants even if you don't plan on taking it because you'll get dings if you are putting time or effort into a proposal but you don't have your summer month or your post you know all of your I mean obviously as a postdoc you're going to put your postdoc salary in there but those of you who go on further in Academia or as a research scientist or is or a position that gets salary from Grants make sure to put that all in don't forget the common items like travel publication fees materials recharge and overhead overhead is the weird one overhead is like the tax that your institution charges on top of your direct costs so if you need 100K at in the UC system you don't ask for 100k you ask for 158k because we have the 58 overhead rate that's money that pays for staff support for the air conditioner for um for the facilities and so on usually your financial staff or will guide you or do it for you like getting all the budget numbers to come out right but it's important to know where all these numbers come from and follow the funder guidelines handling criticism and rejection I can tell you that you don't get you won't get a hundred percent of the things that you don't apply for and if you don't get rejected some of the time you're not taking enough risks and or you're leaving money on the table it's like how a hotel aims for 95 occupancy rate because if they had 100 occupancy rate they wouldn't know where the ceiling was they wouldn't know how much they could be asking for there would be people who would stay at the hotel who can't get in because it's booked and those people have money too so if you don't apply for more stuff and get rejected you'll know that you're you're not uh you're not taking enough risks and you're leaving money on the table reviewers and program managers are not out to get you they only have the budgets for 10 to 20 percent of proposals that get subject they get accepted some criticism is highly unfair and yes that detail might be in there somewhere but the reviewer just didn't find it and that's like it was right in there I swear I put that detail CC and you show all your colleagues and friends like see it was it was right in there and they didn't see it oh sorry um however you're getting a reaction from experts that you're not paying for you're not paying their consulting rate so a professor might charge a company like two hundred dollars an hour say it took three people three hours each to review your proposal it's almost two thousand dollars and like paying foregone payment that you got that work from them for free so pick it for what it's worth resubmit you have a couple of options you can resubmit to the same agency if you get if it gets rejected after making revisions but beware usually the idea itself has to be revised not just fixing the little nitpicks because a lot of times a reviewer will see an idea that doesn't like move them and they're like uh I didn't find this to be that exciting but I can't write that down is it a criticism so I'm going to give the whole Litany of uh too far from their collaborator and the biostatistics and if you just fix all those you're not solving the root problems you got to do something read between the lines and really crank up the torque a little bit and finally no matter how good your idea your preliminary data the strength of your collaborations grant writing is mediated by psychology not always facts it doesn't mean put wrong facts in there but they have to be presented in a way that makes the reader feel smart and delighted grant writing is a necessary part of the process of research chat GPT is as of now not sophisticated enough to do a good job writing a grant that's probably pretty good at reviewing grants based on the quality of reviews that I've received in my life but we won't go there the review the reader is not going to read your mind the reader is not going to study your figures or texts it has to be instantly understandable what you're talking about the whole thing has to be in your face transparent what you're talking about and if you focus on delighting the audience not necessarily getting the funding success will come on average so thank you for allowing me to go over time I'm happy to take questions but after Pizza thanks