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
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?
One of the things I have learned the hard way during my first year as group leader is how easy it is to overestimate the ability of beginner scientists – graduate students, interns, undergraduates – to grasp the “big picture” of the project. Beginners are usually quite good at performing experiments and processing results, but they typically find it very hard to visualize where the experiment fits in the grand scheme of their project. I would like to propose a framework that will make it easier for beginners and their mentors to stay on the same page when it comes to the big picture of their projects. Continue reading
The road of an academic scientist is long and tortuous. Many pitfalls await the hapless young researcher, so any advice is always a great bonus. I have been relying on Twitter and a bunch of great blogs (see my blogroll) to get my fix of do’s and don’ts in academia, and it has served me well – I now have the coveted group leader position at a major university in Poland and I use the blogroll as a constant source of information and support in my ivory tower woes. One of my favorite blogs has always been xykademiqz, written by a successful mid-career group leader in the physical sciences. The blog is filled with great advice and down-to-earth musings on the “human” side of research. That’s why I was really excited when I heard that xykademiqz is coming out with a book, which, as I understand, is a collection of her most successful blog entries organized in a way that will make for an interesting narrative. The book is here, and I got a glimpse of it as an early access reader. Let me tell you this – it is pure gold! Continue reading
The NCN (National Science Centre) website has recently published a report from their April Council Meeting. There are quite a few interesting tidbits of information there, including plans for “mini-grants” that would support scientists that have not held an NCN grant before and who need some seed money for preliminary work or other expenses, such as conference participation. What caught my attention, however, was that the Council discussed the issue of bringing back salary support for technical staff as a legitimate expense in NCN grant budgets. In 2015 there has been a major shift as to who can receive full salary from an NCN grant. Before the change, any team member could be supported on NCN money, afterwards only the PI, PhD students, and post-docs were allowed to have their full salary/stipend included in the grant budget. This was significant, because according to NCN regulations, a post-doc must have received their PhD at most 5 years prior to being supported. Continue reading
I don’t know how common it is in Europe, but I am staggered by the amount of bureaucracy that gets in the way of doing research in Poland. The prime example is the way purchasing of big-ticket items for your lab works. Every single piece of equipment that you want to buy has to go through a so-called public bidding process, where multiple suppliers make offers that match a set of criteria specified a priori by the buyer (i.e. the lab head). Continue reading
The emperor is naked, and yet nobody speaks up. What is the issue here? Why won’t anyone tell the poor monarch that his private parts are on display? That’s the exact same trap many managers fall into – lack of feedback. Once you move up the ladder, whether it be in academia or in the corporate world, you get less and less of it. The reason is very simple – most people you are dealing with depend on you for their livelihood and they will not risk their position by saying what they dislike about your behavior. Continue reading
Go check out Dan Ariely’s TED talk about how people are motivated and demotivated by seemingly trivial things their supervisors do. I think every manager, including all lab PIs, should watch this video. Also, on a similar note be sure to check out Daniel Pink’s “Drive”, which I’ve blogged on before, in a slightly different context.
Another difficult decision that the CEO-PI faces is the decision of what projects to pursue. If the lab is able to come up with a regular stream of data and ideas, soon they will have a bunch of questions they might be interested in following up. Typically the number of questions will exceed the number of man-hours required to answer them, so the PI, hopefully with some input from the team, will have to decide which ones to go for and which ones to can. A bunch of factors must be taken into account when making this decsion. First, the feasibility – is it completely pie-in-the-sky, or is it something that can be done relatively easily? Second, the impact – is the project likely to make a dent in the current paradigms and to be interesting to other people? Third, the available expertise. That one is something that I’ve seen PIs struggle with in the past – they waltz into a project, not realizing that the effort required to build the necessary expertise far outweighs the potential exciting results that might come out of the study. The obvious solution is collaboration, but it definitely comes with a bunch of caveats that not everyone wants to deal with. Fourth, the interest of coworkers in the project – that one’s another hard one. It’s obviously important to have people working on projects they are excited about. If you as a PI care about the project, but the person who actually executes it does not, you’re asking for trouble. Continue reading
As a follow-up to my earlier musings, the scientist-CEO hybrid that is the lab PI must sooner or later face some hard decisions. Assuming they are successful and can attract a lot of funding, they will have to figure out what size lab they want to have. The answer “as big as possible” is the straightforward way to go for many PIs, but I don’t know if that’s always the right answer. Having a huge lab sure has advantages – you are almost always guaranteed funding and GlamorMag publications, you are constantly given honors, invited to speak at meetings etc., but all that comes at a price. A head of a big lab (>15-20 people) quickly loses touch with the day-to-day operations. They spend half of their time away at conferences and invited talks, and the other half scrambling to figure out where the hell the projects in the lab are going. From what I’ve heard from people that worked in such “paper factories”, the lax leadership leads to a lot of frustration on the part of trainees, i.e. grad students and postdocs, who fall prey to in-lab politics and their ambitious but unscrupulous colleagues. Continue reading