Now that you’ve established what your high priority projects are, you should think about how to schedule the tasks within these projects to make the best of your time. Hopefully, you’ve come up with what the skeleton of your project is and how the tree of life is structured. These will be important in figuring out what is more and what is less urgent in terms of individual tasks. Once you have a decent idea of what must be done and in what order, you can start scheduling out your week. Here, I would strongly recommend using the “Big rocks” approach pioneered by Steve Covey (I highly recommend his “7 Habits of Highly Effective People” book by the way). Continue reading
Good planning is absolutely essential in research. It is what makes a difference between a competent scientist who does decent work, and an excellent one who really pushes the envelope. People with poor planning skills will waste tons of time on futile projects and so will not be able to focus on what really matters. While good planning is something that comes naturally with experience, I think it’s useful to have a framework you can refer to at any career stage. The framework I use can be divided into three levels: Strategic planning, tactical planning, and planning of single experiments. Single experiment planning was roughly summed up in my post about “the gory details“, and I will talk about tactical planning in my next post, so let’s get right into strategic planning. Continue reading
In talking to many grad students and postdocs I have found that quite a few find it difficult to prioritize experiments in their projects. Creating a tree of life of a project should help some, but still, the tree has many branches, and in principle one could start with any of them to get to the root. What I found to be a simple solution was to divide the project into “skeleton” and “meat”. The skeleton is the parts of the project that really answer the key question that the project is all about. Think of it this way – would the title of your paper change if the experiment came out one way or the other? If it would, this is your skeleton experiment and it is your top priority. Continue reading
In case you missed it, here’s a storify of a twitter conversation about starting a new lab. It’s full of wisdom for all freshly minted PIs. Some of my favorites are (slightly paraphrased):
You are the best postdoc you will have for many years – stay active at the bench for 2+ years
Your first paper as group leader will be like your first pancake – half baked and lumpy. Don’t wait for the perfect story to emerge – publish quickly to establish credibility and secure funding.
Go read the whole storify if you are starting now or will be starting soon.
As smart as we think we are, we humans are hopeless at objectivity. This struck me as I was reading about peak oil on Wikipedia. I mean the issue is pretty serious. Within the next few decades we could potentially run out of the single most important natural resource that literally and figuratively fuels our civilization. And people, sometimes very smart people, cannot agree on whether something ought to be done right now or whether we have centuries of uninterrupted oil supply ahead of us. Continue reading
There has been a bit of talk on Twitter and among my colleagues IRL and online about work-life balance in academia. See for example this excellent post by @TheNewPI. The gist of it is: is a normal 40h work week, which is the norm everywhere, feasible for academics? I think the answer is yes and no. It really depends on what your goals and priorities are. If you really want to develop an independent research program as PI of a lab at a decent research university or institute, then I don’t think sticking to a strict 9-5 schedule will serve you very well. The more time (up to a certain limit) you put into your work, the better you will become, the more you will accomplish. However, I think there are a few points worth elaborating on here. Continue reading
As scientists we always come up with ideas – solutions to more or less well known problems in our areas of interest. The ideas may be applicable only to our specific project, or they may be general solutions to a much broader set of problems. The more specific the idea is to our area of expertise, the more likely it is to be feasible, but sometimes an outsider can see the problem from a completely new angle and come up with a novel solution that no-one had thought of before. That’s why it’s sometimes good to go out of your comfort zone and try to come up with solutions to problems that are a bit outside your immediate sub-field. The flip-side is that the solutions that you will come up with typically have a fundamental flaw that makes them unfeasible.
I have recently spend a couple of days trying to devise what I thought was an interesting strategy to address a relatively broad set of problems in molecular biology. Turns out, similar solutions had been tried and work only in a very limited set of circumstances. Continue reading
You know those super-expensive accessories that research equipment manufacturers make you pay through the nose for? A while back I bought a pretty expensive Olympus microscope. Since my budget was limited and I really wanted a best-of-the-best objective lens and a state-of-the art camera, I had to find savings wherever I could. For that reason I did not get a filter wheel/shutter hand switch, which is a must if you want to operate the scope without the software running. Having to launch the the cellSens software to switch fluorescence filters was so frustrating that I caved in and requested a quote for the switch. Believe it or not, but this plastic box with a couple of buttons costs almost $1000. Continue reading
Just the other day I was reading a Nature opinion piece on deliberate research misconduct: how it affects the reproducibility science, and what we can do about it. The authors proposed a number of solutions, but most of them focused on punishing the perpetrators. Punishments should be more severe, they argued, the PIs should be held accountable for their trainees’ misconduct, and institutions should be forced to give back money gained by research dishonesty. I’m not sure I agree with this solution. Continue reading
In the previous post I’ve outlined the strategy that will allow beginner scientists to understand the complexity of a research project – something that they often struggle with. From the “tree of life” view of the research project there is a rather straightforward path to understanding the significance and interpreting the results of each experiment that they perform. I recommend that each beginner scientist answers (ideally in writing) the following questions before they even touch a pipette:
- What is the goal of this experiment?
- What is the hypothesis?
- What is the approach?
- What are the experimental groups and controls?
- What are the expected results?