Tuesday, August 31, 2010

Why do I suck?

I'm trying to write my thesis. I really am. I just keep getting stuck, so it's going super slowly, and I'm plagued with guilt about being slow. But every time I try to push myself, to give myself deadlines, to increase the pressure on myself, it just backfires, and I get less done.

I think about what I want to do next. I imagine when I defend my thesis, my committee members may ask me what I plan to do next, and I dream about various answers. I think about telling them that I've realized research is just not for me, and I imagine telling them reasons why I think that. I imagine they might be able to offer some insight into whether I'm right, or whether they might tell me how I could learn to be good at and like research.

But the thing is, my committee, my mentors, anyone who might actually be able to offer me insiders' insight when I say I don't think I'm cut out to deal with failing 99.9% of the time, I don't think I have the vision to seek out the paths that lead to good results, and I don't know how to gain that vision, all the people who might be able to say something to help me are also the people who I need to be references for my future jobs. So I need them to think I've never had a doubt in my life about doing anything, and I certainly don't need to help them come up with a list of my weaknesses. They need to think I'm confident, brilliant, passionate about my career (whatever I eventually decide to pursue).

I've wanted to be good at this. I've wanted to bolster my strengths and improve where I have weaknesses. I've just never really figured out what they are. When everything you do is met with negative feedback, you just change random variables all the time. All you know is, that didn't work; I'll try something else.

I did eventually gain some insight over the years, but I feel like I had to learn everything in the hardest way possible: by doing it wrong in a million different ways. But I continued to evaluate myself, and examine what I could see working (or not working) for other people, and I did eventually improve. But now I just feel too tired of it all, and like it's too late.

I started this game as a smart girl, capable of working very hard. As we all did.

But I was naive, and my whole life, all that had been demanded of me was to do what I was told, the way I was told to do it. And my advisor was a micromanager, so he told me what to do, and how to do it, and how to think about it, and I tried to do it.

But lab work doesn't work that way. What my advisor really wanted was publishable results. And with research, no one knows a priori how to get there.

And anyway, a Ph.D. isn't about that. It's not about just doing what someone else wants you to do. It's yours, your work, your thesis, your Ph.D. But damn if standing up to my advisor doesn't result in insults and threats and extreme unpleasantness. But it's what had to be done to make progress, rather than circling the same microproblem forever. So, difficult Lesson 1 - You can't be a people-pleaser, and Lesson 2 - You may have to endure unpleasantness, insults, and threats and you have to try not to let it get to you.

And then there's Lesson 3, that I'm still trying to wrap my head around. How to choose the right paths to pursue. You see, I'm a plodder. I like to do things once, correctly, and double-check my work along the way. It seemed to work for me in school. But it doesn't work for me in the lab.

I used to do homework with a friend, and I used to say we were perfectly matched as homework partners. He was a racer, and I'm a plodder. He could take our ideas, race through the steps, and see that we were on the right path. I could then plod along and make sure we got all the steps just right. I was not good at the half-assedly racing through to see that it was going to work; he wasn't as good at the details of to plodding along to get all the steps right. It was a great partnership.

But it turns out that the skill he had is much more important to getting stuff done in the lab. And I still suck at it. I've tried. But I feel like I race through the wrong way, choose the wrong steps to gloss over, the wrong results to follow. I race through, choose the path, and then the path is wrong. I do this over and over. How the fuck can I get better at it??? Still don't know.

Over and out.

Wednesday, August 25, 2010

The catch-22 of the unsupportive advisor

Some advisors are universally unsupportive. Others are more selective. The result seems to generally be the same: failure of the unsupported. So the question is:

Do we fail due to lack of support?

Or do we not get support because we are failures?

Wednesday, August 18, 2010

My dream wardrobe

Ok, I know that wardrobes aren't exactly science-talk, but hear me out - this is a minimization problem.

I've never had a lot of money to spend on clothing. I generally don't have a lot of closet space to devote to clothing. And I seem to travel and move around fairly often. I always thought these three conditions were what drove me towards a minimal wardrobe (i.e. a wardrobe that would keep me reasonably clothed while being as small as possible). I realized recently that there's another factor driving me towards this minimal wardrobe: I don't like to have to think too hard about what I wear each day. I don't want an entire department store worth of clothing and accessories to choose from each morning. I want a small, carefully selected number of items. I want my wardrobe to be small so I have fewer choices, and it's easier to get dressed in the morning.

Now, don't get me wrong. I like clothes. And accessories. And shoes. Especially shoes. I like to play around with outfits and looks sometimes, either in my own closet or in clothing stores. But for the everyday grind, I just want go-to outfits that are comfortable and make me feel and look good.

So, my minimization problem is this: what is the minimum amount of clothing a person can own and clothe themselves nicely for a year? That means they have enough clothing in quantity and style to wear for 1-2 typical weeks (time between laundry sessions), clothing for all seasons, and clothing to cover the usual special occasions.

First, I need to define some terms. What kinds of clothing do I need in 1-2 typical weeks? I need clothing for work, for weekends, for work-outs, and for sleeping. For work, I must have comfortable clothing - comfortable closed-toe shoes, outfits I can bend and move around in, some layers for buildings with poor climate control, and nothing that's going to dangle into the dangerous elements of my experiments. For weekends, I do a lot of walking, a lot of indoor and outdoor activities, so I need to be cute and comfortable. For work-outs, I sweat! I need good clothes to sweat in and do tough work-outs. For sleeping, I must have loose shorts and comfy tops. So there we go - my needs for 1-2 typical weeks.

Next, I need to define the typical special occasions. Let's see...We have weddings and funerals, job interviews and presentations. dressy parties and social outings. I also like to swim, ski, and hike. I think that covers the special occasions category for me.

So we have the requirements for typical 1-2 weeks, the usual special occasions. The requirements for four seasons varies by region, but I'd say appropriate shoes, coat, hat, scarf, gloves, light layers and short sleeves for summer, heavier layers including sweaters and long-sleeves for winter. Those seasonal requirements can be fairly universal. So here we go, my minimal wardrobe, below.

For work and weekends:
-1 pair Cute, comfy ballet flats
-1 pair of Dark, straight leg jeans
-1 pair of black pants
-7 casual tops for summer - camisoles, ribbed tanks, short-sleeved T's, graphic T's
-7 dressier tops for summer - dressier short-sleeved and sleeveless blouses
-7 casual tops for winter - long-sleeved t's
-7 dressier tops for winter - thick sweaters, thin sweaters, button downs, blouses
-1 cardigan
-1 blazer/jacket
-1 coat
-scarf, hat, gloves
-14 pairs comfy, no show undies
-2-3 good bras (1 black, 1 nude)
-socks for ballet flats
-belt
-handbag
-sunglasses

For workouts
-Running shoes
-Fleece
-1 pair each of work-out pants: shorts, capris, and long
-1 short-sleeved and 1 long sleeved work-out shirt
-1 great sports bra
-1 pair of great socks
-If these items are the right fabrics, I can rinse them after each work-out and hang dry. If I want to be less gross, I could up the numbers to 3-5 of each item.

For sleeping
-2 pairs of loose fitting shorts
-2 comfy tank tops
-1-2 robes (preferably 1 light-weight for summer, 1 heavy-weight for winter)

For special occasions - dressy
-1 little black dress - sexy but classy
-1 pair of perfect heels
-1 non-black dress
-1-2 wraps/shrugs to go with dresses
-1 suit (can be black pants and blazer from work-wear)

For special occasions - sporty
-flip-flops, swimsuit, swim cover-up, sun hat
-can wear work-out tops for skiing and hiking
-ski boots, socks, thermals, pants, fleece, waterproof shell, gloves, helmet, muffler
-hiking boots, pants (can wear same socks, fleece, shell as for skiing)

There you have it, my minimal wardrobe. So, is this wardrobe what I own? Of course not. But a girl can have dreams, can't she?

Wednesday, August 4, 2010

Notes, organization, and reproducibility

How do you keep notes and records on your experimental methods, data, analysis, and journal articles? What do you keep on file, and where, and how do you organize it? As scientists, we all face the record-keeping problem, and I'm interested in how others deal with it. Over the course of grad school, I've developed my own system in fits and starts, and I'll describe what's working for me.

What to keep, what to keep? There's essentially one reason for keeping things on file: because you might need it later! I know, obvious. But I'd like to break it down a little further, to four reasons you might need it later: 1) it's a result, 2) it's information needed to reproduce a result, 3) it's information that may help with interpretation of a result, or 4) it's information that may lead to a future result. So, as for what I keep on file, I try to keep everything on file that falls into one of those four categories. That's a lot of stuff. How the heck to you organize this stuff so you can find it later when you need to?

How to organize? In the beginning of a project, starting a system of organization is difficult because you don't have a feeling yet for the number of different sub-projects, the scale of those projects, and all of the variables that will change along the way. But, there are categories that will be important when it comes time for publishing and ensuring that you have all the information needed to reproduce your work. For me, those categories are experimental methods, data, analysis, and references.

Where to keep it? I have 3 places. I have lab notebooks - the daily record of what I've done. I have a physical filing cabinet - keeper of everything from written notes and hand-drawings to printouts of journal articles, hardware specifications, and data. And I have a computer (and backup!) - keeper of essentially everything that's not handwritten and a few things that were scanned in. The computer can really get you in trouble with it's infinite space and the myriad bad ways of organizing and naming files. But what I've outlined below works for me, and perhaps could work for others.

References/Journal Articles
I like to keep lots of pdfs of journal articles, and print lots, but not all. I generally make file folders (both physical and on the computer) that represent some general topic and file lots of papers in each folder. For computer files, I like to name the files "(first author's last name)_(Journal)_(pub year)_(2-3 key words)". This system works...okay. I can easily find the papers again when I need to, and it's nice to have hard copies with notes and soft copies for easy access when I'm away from my filing cabinet. However, now that I'm writing, I've started using EndNote, which may cause me to completely overhaul my system. We'll see.

Experimental methods
Experimental methods has been one of the most troublesome categories for me to organize. Methods can be a very diverse category, particularly in biophysics where methods may range from biochemistry to instrumentation to automation. Developing the methods may be a major component of a research project, or even if it's not, methods may change over time. Figuring out how to deal with diverse, evolving methods has been challenging.

Eventually, I determined two keys to organizing my notes and files on experimental methods: subcategorizing, and organizing by date. Over time, I found I generally had three categories of methods: sample preparation, instrumentation, and data acquisition.

For sample preparation, I found it best to type up a protocol, date it, and paste it in my lab notebook on that date. Then I could refer back to that protocol by date and lab notebook page number each time I performed the protocol. As I modified the protocol, I would still refer back to the same protocol, but note the modifications. Eventually, enough modifications would be added that I'd type a new copy, date it, and paste it in my notebook. Eventually, the protocols were fairly settled and each day I prepared a sample, I could just refer back to that date and page. And it worked well for some items I made and stored. Typically we write the date on anything bio-y that we store, and when I used it, or ran out and needed to make more, I could just refer back to that date in my lab notebook. Convenient. Plus, if a labmate wanted to do something similar, they could also look it up and not need me to "remember" exactly how I'd done or made something.

For instrumentation, I had several subcategories that required various forms of organization. I had designs, part specifications, optimization and characterization techniques, calibrations techniques, automation software. I wasn't the best about organizing these things as I went, but hindsight being 20/20, I've learned what I should have done.

1) Keep an accordion of files and a notebook dedicated entirely to your instrument.
2) Design involves a lot of notes, hand-drawings, calculations, references to articles. Date these things and keep them in a folder.
3) Part specifications become impossible to find later. Keep them on file, hard and soft copies if at all possible. (Also, determining what parts are in an instrument is really hard after the fact. Keep records of what you put in your instrument!) 4) Optimization and characterization techniques evolve, and the instrument evolves with them. Write down and date what you do in a notebook dedicated to the instrument (or at least make notes in the instrument notebook referring to where it is written down).
5)Calibrations are very important. Keep good notes on them, by date, in that instrument notebook.
6)Automation software is still a toughy for me. Ideally, it would change rarely, you would carefully track changes by date, and you would keep old copies. Our automation software is all custom written, in a very large suite of software that all works together. I tried to keep notes on major changes, and I tried to keep old copies, but ultimately, I didn't do it that well.

With hindsight, I eventually found the above guidelines to be a good means of organizing instrumentation techniques.

Data acquisition, was generally a combination of the above sample preparation and instrumentation techniques. Generally I prepared a sample and used the instrument in it's present status with the current calibrations to acquire data. And I used some of the automation software I had written to acquire that data. I usually made notes to this affect in my daily record in my lab notebook, with any modifications or variables noted. Those variables are one of the places where things can get tricky, as you often don't even know what the important variables are until you start changing them. But nevertheless, the lab notebook was generally where I noted the details of data acquisition.

Data
Data was actually the simplest thing for me to organize. Our lab had already established a system of organizing computer files by date and time stamp, with a descriptive base file name and different file extensions representing different types of data. I followed that system and found it works pretty well, as long as you follow it. Keeping notes in my lab notebook about the individual files was also key to knowing which files were what. Also helpful: a description somewhere of what's in the different files, and how to load the files for analysis.

Analysis
Analysis was another doozy of an organizational challenge. My raw data files were all nicely organized by date and time stamp, but for analysis, it took awhile to decide how to organize. Did I organize by date, like the data? But then, what about when I wanted to analyze data from several dates together? Did I organize by type of data? By date I performed the analysis? By type of analysis? And how did I organize the analysis programming itself? And what, if anything, did I write about it in my notebook? Or print anything out? Analysis organization definitely presented it's own set of challenges.

Eventually I decided to organize the analysis by date of the data and purpose of the analysis. If I analyzed several days of data together, I just titled it by the multiple dates and grouped it in the applicable month or year. I generally didn't write notes in my lab notebook about analysis, though I wish I had. I often printed plots, and put them in a 3-ring binder organized by data acquisition date and type of data. I wish I had more notes about my data analysis, and eventually I discovered notes about the analysis itself were very important (see below).

Even more important than the top-level organization of the analysis files was putting notes and organization into the analysis files themselves. My analysis software allows data folders, so that I could arrange data within the file by date, timestamp, and type. I also could make notes within the analysis files. I found keeping notes in the form of "date of analysis, goal of analysis, methods of analysis, and results of analysis" were very useful to making the analysis useful to myself later.

A couple more key points
Following the general rules above, I established a pretty decent filing system for myself. I have a lot of files, hard copy in my filing cabinet, soft copy on my computer, and lots of lab notebooks. In keeping this stuff useful, I have a few more key points:
1)Back up your computer files! In at least 2 places, 3 places ideally.
2)Organize your hard copy files. Filing cabinet, tabbed files.
3)Index your lab notebooks. Our labnotebooks had pages at the front for indexing. I liked to list a major category (sample prep, instrumentation, data, analysis, notes), then the specific task of the day.
Also, I found that the more information that was available on computer, the better. Lugging around lab notebooks and file folders sucks. I like to have soft copies whenever possible. Short of scanning in your lab notebooks (or typing all the entries), I found it useful to make an Excel spread sheet, organized by date, that listed what I did on each day that I acquired data. On this spread sheet, I also added in all the important changes made in the instrumentation, sample prep, and data acquisition. I color-coded it in subcategories. It's made finding data sooooo much easier.

Some final notes on file organization for publication
As I write up my work, I've found it very helpful to make a folder for each paper, and within that folder, to have subfolders for each figure or significant result. Each figure or significant result has it's own 1)analysis file, 2)final figure file, 3)data caption file, and 4)data source file. The analysis file has all the relevant data, from raw to fully analyzed. The source file has where the data came from, how and when it was acquired, how it was analyzed, and any important quantifications. The final figure file is the .jpg, and the caption is a caption that would be appropriate for the figure. With this information, I have everything necessary to include the figure or significant result in the the paper.

And that's it. That's my system. What's your system?

Tuesday, August 3, 2010

Shenanigans!

What a great analogy for grad school. The shenanigans of treating Ph.D. students as students when it's best for the university and professors that we be students, and as employees when it's best for the university and the professors that we be employees.

Am I a student? Being a student implies that I'm being educated and trained. That I have an advisor to advise me on how to best obtain *my* goals. That I'm being evaluated in some way that will help me learn and prove that I've learned. Being a student somehow implies to me that I will get out of it what I put into it. That I'm the one invested in this endeavor. My success or failure matters a great deal to me, but should only matter to anyone else insofar as how much they care about me. I know, very idealistic.

Being a student also implies paying for that education. And I don't pay. The university does get paid. The "educators" do get paid. But not by me. By grants. Sometimes by grants obtained by me, sometimes by grants obtained by my advisor. And I get paid by these grants, as well.

I get paid, so I'm also an employee. Employees perform services for pay. They typically have contracts. I have a contract. It's a yearly renewed contract that can be cancelled at any time by me or my advisor. It says I work 20 hours per week on research. I have no allotted leave. No sick leave. No vacation leave. None. Zero, zip, zilch. All leave is at the discretion of my advisor. Renewal of my contract is at the discretion of my advisor. All work is at the discretion of my advisor.

My advisor is also an employee. He performs services for pay. He also has a contract, and though I don't know the details, I know the gist. He teaches, does service, and performs research. He is reviewed on his performance in these activities. He now has tenure, so there is little to no chance that his contract will not be renewed. But his performance is still reviewed for promotions and raises. And his career, the opinions of his colleagues, awards, future grants; all these depend on reviews of his performance. As his Ph.D. student and employee, I have little to do with his teaching and service. But I have a lot to do with his research performance.

My advisor is also supposed to be the person who advises me on how to best achieve *my* educational/professional goals. What happens when his goals and my goals no longer align? What happens when it's beneficial for him to keep me toiling away as a senior graduate student, highly productive for his research, but it's not beneficial for me? What happens when it's beneficial for me to take two weeks vacation to try to recover from burnout, but he doesn't see it? What happens when it's beneficial for me to take a course on teaching, but he sees no direct benefit? What happens when it's beneficial for me to spend time looking for jobs, taking trips for interviews, writing grants for those jobs, but it's not beneficial for him? Then what?

What happens when it's beneficial for me to get out from under these shenanigans, in which I'm a student so that the university gets paid, so that I won't leave because I've invested years in trying to get this degree, so that I work 40+ hours per week more than my contract states, yet still get no benefits such as retirement or health care paid or even contracted leave? What happens when I need to be done with that, but it's not in my advisor's and employer's best interest?