Apr 24, 2020 | Things learned in academia, for the good and for the bad

Today, I would like to list a few things that I learned while doing science for the last 8 years. Some of these habits are helpful and make my life much easier now, while other things actually make my life harder.

First, things that help in the long run:

  1. Maths. I don’t mean the university-level algebra but rather, a common understanding of probability and statistics. While doing science, you need to exercise your understanding of probability all the time. Namely, testing any research hypothesis means coming up with a probabilistic measure to indicate the odds that your hypothesis is true—and, it will never equal 100%. In fact, we can never confirm any theory; we can only falsify it. For instance, let us say that you hypothesize that apples always choose to fall to the ground. So, to test this hypothesis, you let an apple fall off from your hand a hundred times. If at least once it happens that the apple bounces to the side rather than falling to the ground, your theory if obviously false. But if it falls to the ground a hundred times out of a hundred, it might mean that your theory is true, OR, that your theory is still false and that you did not take into account some particular conditions in which your experiment would yield different results. For instance, if you reproduce the same experiment at the International Space Station on the Earth’s orbit rather than on the Earth’s surface, the apple will bounce in any direction rather than falling in the same direction every time. So, in the process of doing research, you can become a very sober person who takes almost nothing for granted, constantly challenges their beliefs, and asks themselves: is this a reality, or is this my bubble?
  2. Patience. Real impact only builds over time. From day to day, from one line of code to another, from meeting to meeting, from one conversation to another, you cannot speed up this process. One day a lot of people will notice your hard work, but before that happens, you can only make small steps every day. In academia, it is very rare that a groundbreaking discovery that becomes viral comes early on in the research career as a sufficient level of expertise in the field is necessary to build up upon. With getting an academic achievement it’s different from many other types of success, let’s say, getting rich. In science, you cannot inherit any assets after your grandparents. You can’t win a lottery. You can’t record one funny movie with your cat that gets viral on YouTube. There are no shortcuts here. Of course, there are some professors who become well known mostly because of their great networking and diplomatic skills, or because they accidentally made a huge discovery, and not because of their research skills, but in their community, they function more like a good topic for a joke than as role models. Even though they earn their salaries, they aren’t, in general, as respected as those who reached by putting on an enormous workload and producing a lot of good, original research. To persist in science to long, you would also need to build a strong network of personal contacts. Building personal networks in science is much slower process than it is in business because the frequency of external meetups and conferences is lower than in business (they usually happen a few times per year). Therefore, to build a stable network in science, gain some following, and develop a personal brand in your research field, you would need at least 5-10 years of focused work — and often much more. After spending a few years in science, it becomes obvious that while starting any project, you should prepare for along and bumpy ride.
  3. Not afraid of hard work. Academic jobs are not 9-to-5 jobs. Some people in science claim that they indeed work 9-to-5 but I always doubt when I hear this. Even as a PhD student with one main project and 2-3 undergraduate students to supervise, I used to have issues with managing all my duties as fluently as I probably should, and given how many meetings, lunch breaks, and other events we used to have at work, closing the office door behind at 5 pm and forgetting about work was just unfeasible. So, I cannot imagine how professors who have 10-20 PhD students and 5 Postdocs to manage, plus courses to teach, grants to write, and a lot of bureaucratic and representative duties next to this, can possibly even close their door at 5 pm. Academia is a bit like a Shaolin monastery — the necessity to work hard is as obvious as the necessity to breathe. So, during graduate school, you can acquire the working ethics for the whole rest of your life. And, that becomes useful down the line because you never cry over yourself and over the fact that, to get somewhere, you need to work your butt off in the first place.
  4. The realization that your output is not proportional to the effort you have put into the project but rather, to the size of your audience, a.k.a., “impact”. It is not true that to produce a high-impact factor research paper, you need to be a genius, be extremely lucky, or work hard on one subject for twenty years. The impact of your work is primarily a function of how many people are interested in reading the results of your study — and not of how much effort you need to put in the study. For instance, it is often the case that researchers who ask very fundamental questions, apply standard methods for data analysis to new, high-quality, large (e.g., psychiatric) datasets, and produce beautiful, colorful figures, publish very high and get a lot of citations. In this case, the difficulty is not how to overcome challenging obstacles in the research process but rather, how to become the person who lands this research project — as when the data is collected, many people around will probably be willing to do the same study on this dataset. And, it often becomes more of a politics than research. I do not intend to rant at science right now; I just mean that to make an impact in science, it is good to learn the game and think of research projects business projects: what is the estimated effort, what is the estimated chance of success, and how many people in the field are potentially interested in learning about this topic. The complexity of the research pipeline and the ambition to do something novel are of minor importance for the overall outcome of the project. I keep this in mind now whenever I think about what to do next. I have lots of hobbies and interests that I could potentially make my way of living – but some of them are so niche that I would have a hard time making for a living out of that. Working on jobs is a type of activity that naturally makes a lot of impact; at the end of the day, most people only really truly care about a few things in their lives — their health, their relationships, their kids, and their job. So, if you come up with any possible lifehack, product, a new piece of knowledge, or an education program that could influence one of these areas for the better, it will most likely be of interest to lots of people. And, this might be something really simple, actually.
  5. Don’t cross people, just walk away. What I also learned in science is that it is better to avoid conflicts at any cost, and if someone cannot appreciate your value, better to change the environment and find someone else who does. Standing on your eyelashes to make someone else like you, has no point at all. Plus, 80% of the people who you ghosted and leave behind, will at some point come back with a much better attitude anyways. Oh, one more fact: acknowledge people even if you don’t personally like them; it costs pretty much no time and effort and pays back 100-fold.
  6. Be prepared for problems and for the critics. In academia, you are not constantly praised and sugarcoated unlike in most private companies where managers aim to create an atmosphere of teamwork, appreciation, kindness, courtesy, and respect — almost a family vibe. In academia, for most of the time, you are flooded with “constructive critics” and you are on such a dopamine hunger that every time you get actually praised for what you do, it is time to celebrate. After a few years in academia, one has quite a thick skin and does not get depressed because of personal critics too easily.
  7. The notion of currency in academia is not a simple concept. Normally, you do your job and you get paid for it. Then, with time, you acquire a portfolio of projects/positions and get promoted/paid better. But in academia, the picture is much complicated. You write publications to acquire prestige, grant money, and more people to do your projects. You don’t get paid at the point when your work is finished but rather, when you promise to do a project (i.e., write a grant proposal and that proposal gets accepted by the associated government agencies). There is a lot of hidden agenda, i.e., people making informal deals and sharing projects to maximize their personal output (i.e., the length of the publication list) per person — which, in turn, maximizes the chances of getting the next pool of money. This means that when you enter the new research environment, you need to understand the rules, what are the relations between people, who is really important to you, and who is not. I learned this one the hard way, and during my PhD, it took me way too much time to realize that just doing research is just not good enough if you don’t have a good understanding of the environment that surrounds you, especially of this hidden layer of connections. Now, whenever I enter a new environment, I am trying to understand the relations between people, what the local currency is, and what is really important/not important for long-term success in this working culture because I know that this knowledge will probably have more impact on my quality of life than how good my work actually is.
  8. Inverted imposter syndrome. In academia, most people have the imposter complex. This basically means that deep inside they all feel like underachievers — or, that they even feel plain stupid. As a matter of fact, regardless of how smart you are, there will always be someone even smarter than you out there. For this reason, we are always told by our superiors over and over again, “Don’t worry, you are much better at what you are doing than you think you are.” This phrase stuck to me. Now, whenever I fear to do something new, I tell myself that from the objective standpoint, the chances of succeeding are probably higher than it appears to me. And then I jump.

Now, a few words about the things that actually make my life harder:

  1. Share — no share. In academia, you openly reveal your full research pipeline online after publishing your article. The Open Science movement made big progress here over the past few years, and now — unlike ten or twenty years ago — it slowly becomes compulsory to reveal all the details of all your solutions and all the research steps undertaken to get to these solutions, to public. This makes sense as scientists are paid from public funds, and, at least in theory, they all serve to the society. There is nothing to hide! For more, as scientists, we use to attend international conferences where we present not only our published work, but also the fresh, original, often half-baked results that we hope to get published in the future. There is an atmosphere of trust, and even though scooping happens once in a while, it is so rare that most people choose to take a risk and openly talk about their research plans and open research projects. This is not how things work in business though; you need to be much more paranoid here and keep your cards close. I adore openly chatting about what I am doing at the moment, so I often need to cut my tongue when it comes to business contacts. After spending so many years in academia, it is so hard to now close yourself from other people, and stay quiet when you are really excited about something that you are doing! Also, now I have a company, whenever I do research, I cannot really reveal the pipeline and statistics that lead to solutions I present. What was once the reason to be proud of, now becomes “the know-how of the company,” and is all wiped under the carpet.
  2. Monetary exchange. In academia, when you enroll a friend onto your project, you append their name to the list of authors on your project. This means that you share the prestige, and the research achievement — it is a non-monetary exchange. In business, whenever you ask a favor, you should pay back in some way, either by plain payment or by returning the favor in some other way in the future. It is quite a mental barrier to start paying to people you know as this feels like morphing friendships into something really weird. I am still on the learning curve as it still feels unnatural and weird to me.
  3. Slow decision making. In science, the cost function to evaluate how you should allocate your time contains the “quality” component only. If you need to spend an additional year to make sure that one of the assumptions in your model is correct, so be it! In the real world though, you need to stay vigilant as the market and the opportunities change/come/go way faster than in academia. Sometimes, this means making compromises on the quality, as the cost function you are using to make decisions, must contain also other factors such as time. I am still in the process of learning that overthinking things does not make sense and that you should just put your ideas to life instead of spending months on planning, trying to predict any possible problem, and worrying if you have an optimal solution to some problem already, or you still need some more work.
  4. The assumption that you are smart and rational, so you are immune to cognitive errors. As a scientist, you are constantly being told that you are smart. For most people in academia, this was he case from a very early age. This makes us prone to certain problems. When you get out to the real world, you can be much more naive than people who have been living in the real world for a long time now. People can trick you into working for free, or easily steal your money just because you have too much trust that what people tell you, in actually true, and that their intentions are clear. Outside academia, I learned that I am an idiot of sorts and that if I don’t learn how not to select people and projects properly, I will land on the street. Still on the learning curve.
  5. The tendency to invest all the time and energy in one aspect of life. I always admired people who are able to live in a harmonious way and take care of their professional life, health, wealth, social contacts, entertainment, and spirituality at the same time. You probably know the stereotype of a dizzy scientist with a 5-day beard and in a fatigued sweater. Well, this is not just a stereotype. In academia, your individual research performance in so important that most people tend to deemphasize many other areas of life on behalf of the research career. They do not exercise enough, don’t take enough rest, stop reading anything unrelated to their work, stop making friends with people outside academia, and stop taking any time off for thinking about their life from a perspective, or simply daydreaming. They often focus on practicalities, and especially, on building their professional portfolio. This is, of course, a short-lived strategy and, in the long run, leads to exhaustion, depression, and feeling lost in your life. I also still have a tendency to be a maniac about what I am doing, but I am trying to find some internal peace and harmony.

What did you learn in science? Which of these skills/mental states help you now? Which of them make your life harder? I am curious to learn! Please share with me, either as a comment under this post, or in a DM.

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Please cite as:

Bielczyk, N. (2020, April 24th). Things learned in academia, for the good and for the bad. Retrieved from https://nataliabielczyk.com/the-jobs-of-the-future/

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If you would like to read more about careers (for PhDs and other white-collar professionals) and effective strategies to self-navigate in the job market, please also take a look at the blog of my company, Welcome Solutions where I write posts dedicated to these topics.

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