This post contains the last three question. The final two concern the phrase "your scientific approach", which I found a bit vague. I asked my PI for clarification, and he responded:
We all employ short-term and long-term strategies to achieve our goals. These include our working habits, the way we think about scientific questions, strategies for surveying the literature, the way we set up experiments and controls, the way we analyze data, and how we set ourselves up today for questions we want to address in the future.
All in all, I found this exercise to be quite useful, and would encourage anyone reading this to mentally answer the questions for themselves. Anyway, here are the last three questions.
What are your goals and milestones for 2016?
If 2015 was about gathering my research tools, then 2016 is about applying my new skills towards my project. That isn’t to say that I think I can quit getting better at programming. I hope that next year, my code has improved as much as it did in the last 12 months. All of the shortcomings I previously listed, for example, are on my TODO list for 2016.
This coming semester is going to be full. I want to learn a lot from my final class, Object Oriented Data Analysis, which should teach statistical techniques for high-dimensional data. Similarly, I’m hoping that the three classes I’m TAing will provide useful review opportunities and reinforce what I learned last year. Finally, I plan on not simply passing my oral preliminary exam, but using the preparation time to read and retain as much background literature as possible. I hope that I will stay focused enough to gain a full sense of everything that has been published in relation to my project. Hopefully, this clearer view of the field will then allow me to even more precisely define what research questions I am addressing.
By beginning of summer, I plan on having a logical list of analyses to code and run. My goal for summer, then, is to minimize distractions and plow through the code. Again, I already have a well-defined project and a pretty good idea what the analyzes will be, but orals should set me up to be exceptionally productive (in terms of research results) during the summer months. By the end of the summer, I would like to have enough high-quality data to publish in a medium impact journal.
This coming Fall, I should have no obligations in terms of classes, TAing, prelims, ect. I would be disappointed if I didn’t have a paper submitted by the end of the year. Projecting this far into the future is a bit difficult, but I think Fall should be broken into two section. Assuming that summer goes as I have outlined above, it seems appropriate to take some time to tie up loose ends and follow any especially interesting leads. In other words, I would like to take the first half of Fall to see if we have any data or insights from the summer that launch us into the high-impact range of journals. The second half of Fall should be spent writing; I don’t think it’s far-fetched to plan to have a full-fledged paper out the door before the Holidays.
What aspects of your scientific approach will you look to maintain in 2016?
Overall, I’m quite satisfied with my current scientific approach; I’ve gotten in a pretty good groove. Here are a few points I hope I keep up next year:
I’m optimistic and enthusiastic about my project. Too many graduate students don’t seem to enjoy their work for one reason or another, which hurts productivity.
I have a schedule that works for me. I may come in a bit late, but I stay fairly focused throughout the day and evening, and usually manage to pump out a few more hours of work from at night before bed.
As I outlined in my ‘met goals’ section, I’m doing well at developing my analytical toolbox.
I’m generating logical and worthwhile research questions at a decent pace. A lot of them don’t pan out in the long run, of course, but I want to keep coming up with new questions.
While I wish that I would simply make less mistakes, I want to continue to be conscientious enough about my analyses that I catch my errors sooner rather than later. Just because I generate a set of numbers doesn’t mean I quit thinking about the code or the problem.
On a final note, I also want to make sure I stay generally healthy. Nothing makes it harder to do good science than being sick.
What aspects of your scientific approach can you improve in 2016?
I’ve always considered my propensity towards carving out quiet time one of my greatest intellectual strengths. Finding some time each day to reflect or just let your mind wander over the terrain of a problem is a critical component of creative problem solving. Creativity, in turn, is often necessary to overcome a difficult problem or see what everyone else is missing. Unfortunately, over the past few years, I have been finding it more and more difficult to make time for silence.
There’s a popular internet-term, ‘shower thoughts’, which describes the phenomenon I just mentioned. What I find depressing is the probable etymology of the term. Showers are literally the single time in any given day that the average person spends without mental stimulation. Therefore, it is the only time when people come up with little treasures like ‘The object of golf is to play the least amount of golf.’ Everyone recognizes how busy modern society is, but we don’t fully appreciate how damaging constant visual/auditory input is to our deeper mental capacities.
So, this year, I want to make more of an effort for making the time to just sit and think about my project. This means I’m not listening to music, checking notifications on my phone, or talking to people. It also means I’m not coding, reading new literature, or watching a Python tutorial. I’m only thinking about the project. I honestly think this is the single biggest improvement I, or virtually anyone else, could make in my/their scientific approach for 2016.
We all employ short-term and long-term strategies to achieve our goals. These include our working habits, the way we think about scientific questions, strategies for surveying the literature, the way we set up experiments and controls, the way we analyze data, and how we set ourselves up today for questions we want to address in the future.
Below are a few smaller improvements I want to make:
I want to spend a bit more time each week reading literature, particularly in small doses.
Sometimes, in the interest of time, I skip on computational controls because I assume I know what’s going on. It’s worth coding in more controls.
In the interest of health, I should spend more time exercising.
Overall, I want to be more deliberate and efficient with my time.
