I have to make a call on whether or not to submit a grant proposal this round. This is a proposal that has been in twice already and was hit with the "needs more data" tag in the most recent round. I have a good amount of new data but am waiting on a significant bolus of data that should be arriving next week. The deadline for the proposal is Jan 12 and oh, did I mention that I'm submitting a second proposal that week?
If I do send this thing off I'm planning on significantly re-working it to streamline the presentation and change the data collection to make the study more comparative. This will be fairly straight-forward and I have some useful data in hand that should help my case, but I don't have the mother load yet and it may not come before the deadline.
If that is the case, I think I have the following options.
1) Submit the re-worked grant to the same program and then send an update when the data arrive. This is the most conservative strategy, but I run the risk of pissing off my PO if I don't have those data because I told him that I wouldn't re-submit without the data I am waiting for. This is probably a minor concern, however.
2) Submit the re-worked grant to a different panel and submit the update. This has some appeal because there is a new panel that my proposal would fit nicely under and I could get away from banging my head against the same wall.
3) Wait a round, gather everything I need to make the grant as solid as possible and then submit over the summer. Although this would probably be preferred by my PO, it makes me a bit itchy. At the same time, I don't want to kill myself over the next two weeks to submit something that's not going to have a shot. What if the data I am waiting on don't work out like I expect?
My inclination is to submit it again and make the best of it. If I don't see those data before the deadline then I may be best off going with option 2, but I think I have changed my mind between all three options about twice a day for the last couple of days.
Data management is one of the most important skills we learn as researchers. Without it we are well and truly screwed and can spend days slogging through a mess of our own making or have to re-do experiments altogether. But other than training I have seen on either databasing programs or as a small section of course in Unix, where does training in good data management come from?
In my own experience data management was something learned on the job that became more complex as the amount and breadth of data grew. Often this was a gradual process that allowed for the trainee to scale up from a base and each person came up with a system that worked well for them. An obvious issue with this is that multiple systems in a lab can become problematic for data sharing, but as long as the final product is in a "sharable" format this is not a major problem in most circumstances.
In my field however, things have changed. Yes, my students no longer have to walk to work uphill both ways in the snow like I did and nothing costs a nickel anymore. Now, the sheer volume of data we produce for a project is enormous compared with the data I dealt with as a student, so the gradual building of a database is not so gradual these days. Data management is more critical than ever, but it never occurred to me until recently that simply saying "Make sure you keep your datasets organized and well labeled." about 100 times isn't enough.
So, as part of my supervisory tasks in the coming year I'm going to start sitting down with all my students to go over their data management and ensure they have a good system in place. It may take me some time, but ultimately it'll save a lot of person-hours down the road.
I'm sure others have dealt with this in the past as either the teacher or the trainee. Any particularly effective strategies? I realize that the type of data matters, but I think it's worth discussing.
Here we sit with one week left in the Science Blog NFL Challenge and suddenly things look interesting. Much like her beloved Vikings, DGT was stumbled in the last few weeks, looking vulnerable at the wrong time of the season. Could it be that she is feeling the strain of the long season? Hard to say. But what is not hard to say is that having built a lead that looked unsurmountable a couple of weeks ago, DGT has tumbled within striking distance.
One week remains and DGT is clinging to a 1 point lead, with Nat smelling blood. Somehow I've managed to stop the bleeding and put together a solid three week stretch to pull into third place, 4 points off the lead. As your week 16 winner, all I can say is that I have my eye on the prize and not the minor victories. Trailing two point behind me is a logjam of Chall, Alyssa, PiT and last week's winner (sorry for the delayed gratification), Candid Engineer. Odyssey and Genomic Repairman are three points behind the traffic and 6 points behind them is Tom trying to drive with the "check engine" light on.
Will there be a massive upset next week or will DGT find her mojo and bury us all? Could she be toying with us just keep it interesting? The thrilling conclusion* next week....
*And the final end to these posts for those of you who have no idea what I keep going on about.
Holy shit. I just took a whole week off. Not a week to travel to do work or attend a conference, but a week where I traveled to a warm place and spent time with family (all 37 of them!) and didn't do work. Alright, so there was some work done and that phone call to an NSF PO, but relatively speaking it was a workless week. The first one since starting this job.
It was good. I needed it. But now the serious shit starts again. The only question is where to begin?
There's the minor matter of responding to a couple of small comments on the short piece I turned in two weeks ago. There's the bigger issues of the grants I have due, restrategizing one of them and figuring out if I need to travel over spring break for sampling for the new plan. There's the looming issue of teaching my first class starting towards the end of the month and there are the dozens of little things hanging around like trampled confetti the day after a party.
I'm not going to lie, the next few weeks are going to suck. In a major way. But it was nice to get away for a little bit, to spend time with family and to have all that time to play with the Wee One and hang out with my wife. It was a good week.
Time to clear the cobwebs and dig back in.
After this weekend my family and I are heading out of town for a few days before the push starts to get two grants written for the Jan deadline. A few days away (including 5 flights with the Wee One!) before the madness begins. I thought I would just wish everyone a good holiday season and safe travels if you're going anywhere.
In the spirit of the holidays I thought it might be a good time to invite the many lurkers that pass through here to say hello. Roughly 1200 - 1500 clicks land here every week and yet there are probably 20 or so regular commenters, most of whom write a blog themselves. No, I'm not sick of those follks, but I would like regular readers who don't normally weigh in to say hello and describe yourself as generally as you want. At times this gig is a conversation and at others it feels a bit like performance art. I don't mean that as a complaint, but simply that on occasion it's nice to get some feedback from the silent majority.
In a way, I guess this is like an earlier post, but this blog continues to evolve for me. I'm not sure how it will change in the new year. I am considering blogging a bit more about topics closer to my research heart, but must still wrestle with the issues that come with paving an internet path to my lab door. Inevitably I will end up becoming less pseudoanonymous here, but I'm not sure when or how that will happen just yet.
So, Dear Readers, what topics would you like to see discussed more here? I'm sure there are things that I haven't even thought of that might be useful to many. Would more science be a good thing or is the process of growing into this job far more interesting than what we actually do in the lab? It's entirely possible that those who do frequent this dive come because the topics discussed here are the ones they care about, but here's a chance to weigh in.
I'm teaching my first undergraduate course next semester. There's been recent discussion about new profs having to learn to teach on the fly and I certainly fall into that category. I've done the TAing, took a course on teaching, did the guest lectures, blah, blah, blah, but I've never been responsible for the material in an entire undergraduate course before. So, I essentially have zero experience here.
This is not a new course and it is an upper-level class in my field, so it's not like I'm teaching anything unfamiliar or being pushed in front of 700 freshmen. It'll be a lab course with roughly 30 students who will mostly be in their third year. To make things even easier on me, the person who previously taught the course gave me everything they had from the last few years. Merry Christmas.
Even with a lot going in my favor, I have no doubt that my inexperience will show to the students. There will certainly be a number of situations that I will not have thought of or be prepared for in the first go-round and I can't pretend that the course will be delivered flawlessly. Is there any situation where a person does their best work with the least experience? Probably not.
Do I pretend to be the seasoned veteran that I am clearly not in front of the students or do I acknowledge the obvious right off the bat with the them? My first reaction would be to let the students know and encourage feedback early in the semester with regard to the pace and delivery of info. In a lot of ways it seems ridiculous to try and hide my lack of teaching acumen, but some have told me that admitting that I am teaching for the first time is inviting problems. I can see how certain students would seize on such an opportunity to complain about any number of things, but likely that the class is too difficult. At the same time, I don't want to find out in the end of year evaluations that I was doing something critically wrong throughout the semester and that no one ever mentioned something that could have been easily fixed and would have improved their experience. As with all student-based evaluations, it's a fine line and I have no intention of catering to every student whim as the semester goes on but am willing to be flexible.
For those of you with teaching experience, what are your thoughts here? For the students out there, how would you react to a prof admitting to being inexperienced and offering to work with the students throughout the semester to make sure they get the most out of the class?
The ginormous book chapter that had been stalking me for months is official done. Just shy of 20,000 words, mostly vomited onto pages during the few blocks of time I could carve out to do the work. It wasn't a fun experience, but it's done now and I think it's a decent contribution. Will anyone ever read it? Who knows.
Not 2 hours after sending in the almost final draft of the chapter, I got an email from the coordinator of a workshop I went to over the summer. He wants a 1,500 word (incl refs) piece... by the end of the year. Although I was loath to open a fresh document and have that blank page staring me down, my first thought was that 1,500 words would be like sneezing after finishing up that mammoth book chapter. I figured I might be able to pull it off in an afternoon if I had an uninterrupted one, but it's an entirely different way of writing and my head is in 20,000 word mode.
I have to confess that I write differently than some - I'm kinda like the Colts in that I have strong first drafts. More often than not I labor over the original piece but then don't do a whole lot of editing later. That type of writing is conducive to a giant book chapter, but not so much to a tight piece that has to be written and reworked to fit into a tiny package and still get the message across. So, despite my initial reaction to this short commentary manuscript I'm suddenly finding it exceedingly difficult to completely switch my writing style to fit the new constraints. I wrote what I thought would be a brief introduction and have already used up 350 of my precious words.
It's like having to give a full seminar and a 12 minute conference talk in the same week. The short talk looks like an afterthought until you remember that those are some of the hardest talks to make cohesive and understandable. So much for my "afternoon manuscript".
Only three weeks left of the regular season and three more weeks of the NFL pool. It's the home stretch and the last chance to claim the glory associated with winning the prestigious Blogger NFL Pool Final Trophy.... which will totally be different from the weekly trophy... let me just google around a bit.... yes... totally different.
With the pressure increasing almost everyone had a good week this week. The scores ranged from 7 to 13, which is the highest score we've seen this season. Part of the higher scores is that there are no teams on a bye from here on out so more games are being played, but 13 is still impressive.
DGT remains the leader with 110 total points, but faltered a bit with 9 points this week. Nat made a huge move with a score of 12 and is now only 4 points out of the lead. Odyssey also had a big week with 12 points and managed to triumphantly emerge from the basement (poop deck?) to claim 99 points on the season so far. PiT remains in contention with 104 points and Alyssa's score of 11 moved her into 4th with 102 points. I also managed 11 points this week, but still lost ground because this weeks winner tied my total core of 100 with his 13 points this week.
This week's winner is Genomic Repairman. Can he make an underdog run at the title? We'll see.
Go over and show Alyssa a little support this morning.
Last year was my first recruiting year and everything was a mess. No one told me that applications had to be in to our grad school by January until the day before the deadline and that just started everything off on the wrong foot. I advertised a position on several listserves and the response was lukewarm, maybe even lukecool. I corresponded with a couple of applicants, but for various reasons those discussions dissolved and I ended up taking on a student from the pool of departmental applicants, who did not get accepted to a different lab in the department that they had wanted to go to. It's worked out well, but that wasn't exactly how I expected things to go.
This year has been totally different. I have several highly qualified applicants who have already contacted me. Some have experience in exactly what we work on and others have experiences that would help them take on the data from a couple of our projects. I could easily accept a few of the students who I will have to decide between and hopefully I will have the opportunity to take on more than one.
What's changed? In many ways not a lot. The lab hasn't published much of significant impact this year, so certainly it's not that students this year are suddenly exposed to our published brilliance in ways that students last year could not have been. We had a website up last year the same way we do this year and we don't have any more of a web presence.
But perception has changed. I think it has to be that it took the community here a bit to catch up to the fact that the lab was up and running. Most of the applicants (though not all) this year know someone doing research in our field who suggested they take a look at the lab. Last year everything was just getting established and it wasn't until the conference season this year that we were fully geared up and I had students presenting data at meetings. I think that was the tipping point in terms of other researchers fully recognizing that I had moved and established my own shop that they could suggest that their students check out.
It's great not to have to work to get students interested in the lab, but have them contact me. I already had one student in mind for this application cycle, but now it looks like I'll have a bunch to chose from.