How To Manage The Expected Pace Of Work In Scientific Research

How To Manage The Expected Pace Of Work In Scientific Research
2 years ago

How To Manage The Expected Pace Of Work In Scientific Research

I’ve always been curious about the pace of work in scientific research. The technology we have – literally – at our fingertips enables us as researchers to be more efficient and more productive than ever before. But I do wonder, is this actually good for science? And perhaps more importantly, I question – as a neuroscientist – is it good for us?

How technology shapes scientific progress

Previous studies have shown that giving employees computer training can yield a three to five times greater payoff in productivity compared to other investments. This payoff is due to increased efficiency and, as is easy to imagine, makes otherwise mundane tasks like sharing documents and storing data much easier. In research, no longer do we have to trek to the library to find that foundational paper in a journal from many years ago. Instead, we can find the paper on Google in an instant and start reading it a minute later. Moreover, as computing power has increased, so has our ability to analyze complex datasets with innovative image or signal processing algorithms, sometimes even employing advanced techniques such as artificial intelligence or reservoir computing.

Of course there are many, many advantages to technology. Performing statistical tests in MATLAB saves hours of number crunching, which when done by hand is more prone to error anyway. In the social sciences, collecting survey responses can be accomplished – often for free – using online, secure services and does not require printing thousands of surveys anymore or stamping self-addressed envelopes. These, among others, are clear advantages that technology has given us.

But are we missing something by not taking that trek to the library? Since we have less mental downtime – for example, between deciding to look for a paper and actually being able to read it – are we failing to think as deeply about our scientific hypotheses? We no longer have to trace by hand every dendrite on that neuron or find every spike in that recording – computers can do that for us faster and often more (or as) accurately than we can. But is not having to do any of these mundane tasks always helpful for science, in the end? Even if we can (in theory) graduate faster or churn out more papers per year, are we missing something by not allowing our minds to wander?

What about technology shaping our brains?

While technology has changed rapidly, our brains have not been evolving the same way – this is not to say that technology isn’t changing our brains. In fact, we know that technology-induced changes are indeed occurring in our brains. Information overload causes us to pay attention to trending news stories for a shorter amount of time. Moreover, due to faster deliveries for online orders and constant interaction via social media, we expect instant gratification – even if it doesn’t make us happier in the end. But – our brains aren’t thinking more efficiently, the way that sending a document via email makes us more efficient than having to send it by snail mail. Our brains have not evolved to be more efficient in order to keep pace with technology, so how do these two facts of modern life – more efficient technology but the same thinking brain – work together?

This blog post is not intended to be nostalgic for “the good old days” – as a millennial, I grew up with computers and the internet. Rather, this piece is a call to question the pace of work in research and to be realistic about the rate at which we can expect to have brilliant ideas. For example, when I’m thinking deeply about something, I still write it down in a notebook. This way the ideas flow more slowly, more deliberately, and the act of physically writing instead of typing helps my deep thinking process.

So, all this philosophy aside, the reality of technological advances in science is that sometimes (often?) we are expected to accomplish more than is possible, both in terms of our time and in terms of our mental capacity. So how do we manage expectations – our supervisors’, our colleagues’, and our own – and embrace the realities of modern life while also enforcing our own boundaries?

How to set and manage expectations in this technological world

The advice I am about to share below was learned the hard way when, for two years at the beginning of my postdoctoral training, I was a joint fellow at the University of Maryland (UMD) and the National Institutes of Health (NIH). Because I could run analysis while doing experiments and attend meetings via WebEx (before this was the new normal!), I threw myself into the work, didn’t say no to any opportunity, and basically expected I could be a full-time postdoc in two places. Please note that my advisors did not put this expectation on me – I put it on myself.

For two years, I was constantly running between the two labs in Bethesda, MD, and College Park, MD. While they are not far apart geographically (approximately 14 miles driving distance), it was very disruptive to rush out of a meeting in one lab during the afternoon, race across the Beltway to the other lab, and set up an experiment that evening for the next day before doing it all over again. It left me ragged and burnt out, and it took me a solid year and a half to realize it. The conversation of going full time in one lab was difficult, not only because I felt like I was letting myself down – I wanted to be able to do it all and then some (regardless of how unrealistic this expectation was) – but also because I knew one of my supervisors would be disappointed.

Now I am a full-time postdoctoral fellow at UMD and have maintained a strong partnership with the lab at NIH. I am not only happier but also more productive. While my day-to-day satisfaction is largely due to the fact that I only have one office, one set of meetings to attend, etc, it is also because I have finally learned how to manage my own expectations and how to set achievable goals. What follows are some of the lessons I have learned in the process of getting to this place.

1. Start with big picture goals

What do you want to accomplish over the next six months to a year? Be as specific as you can. How many first author publications do you want by next year? How many grants do you want to have applied for? Write down your goals to make them real and re-evaluate every month or so.

2. Make your week-to-week schedule with the big picture in mind

Once you have your big picture in mind, figure out what you need to do each week to get there. Be as specific as you can with your tasks. I found that writing “finish X paper” on my weekly to-do list didn’t work so well, but “set up data analysis for figure Y of X paper” was much more effective. Moreover, having your big picture goals in mind ensures you don’t lose sight of them in the week-to-week slog.

3. Set boundaries for yourself and others (supervisors, mentees, etc.)

Absolutely critical to not getting burnt out in research is to have “off time”. Email at our fingertips can be very useful and also very damaging. Set boundaries not only for the obvious events like meeting times but also for checking email or responding to Slack messages. You don’t need to be constantly available, and if someone really needs you, they will call you, not email you or message you on Slack. Adopting a reasonable policy like this – and sticking to it – will be better for your mental health and will also set a great example for any mentees you have.

4. Reward yourself for achieving goals, even small ones

The constant grind of science makes it feel like our work is never done. In college, my mom used to ask how much work I had to finish that day. Since work came in discrete amounts – a problem set, studying for an exam – the answers were straightforward. These answers became less obvious in grad school when I was focused full-time on research and has continued into my postdoc. The answer was often: “I always have more work than I have time.” Carrying this realization all the time can feel overwhelming, so one thing I’ve learned (related to point 2 and being specific with your to-do tasks) is that when you do finish figure Y for paper X, reward yourself! Get some ice cream, or a beer, or go for a walk. Celebrating the small victories will ensure you feel like you are progressing and not just on the hamster wheel.

5. Be kind to yourself when you don't meet a soft deadline

In addition to forgiving yourself, also honestly ask yourself what went wrong. Did you overcommit to other, unimportant tasks? Were you not feeling well, physically or mentally, and just couldn’t operate at peak performance? All these reasons, and others, are completely understandable. If you consistently don’t meet your own expectations, perhaps they are too unrealistic – try introspecting to figure out what is actually reasonable to finish on a week-to-week basis. This is something I still struggle with because I know what my productivity can be “in a vacuum” (i.e. high school or college Kate with no additional responsibilities), but taking meetings, mentoring, and personal/family time into account will take away from the time you can actually spend working. And you know what? That is both absolutely fine, 100% necessary, and will make you a better-rounded human in the end.

6. Recognize when it’s not possible to catch up

Sometimes we really bite off more than we can chew – not as in you didn’t quite finish all your data analysis before your presentation at a group meeting; more like you can’t make progress on a project for months because you are completely overwhelmed and totally overcommitted. When this happens, be honest with yourself. Remembering the previous point, it is important not to beat yourself up. Introspect and figure out what went wrong, whether it’s over-commitment to projects or reduced capacity for work due to life events. Be honest with your supervisors, mentors, and/or collaborators. Ask for help and/or forgiveness on those missed deadlines, and offer a plan for getting back on track. Many others have been there (or at least know someone who has), and you will be surprised at how understanding people can be. I had to do this with a project last year, and while I felt terribly guilty, the response from everyone involved couldn’t have been more positive. This helped me to seriously reevaluate my commitments and to slowly catch up on everything, including this blog post!

In closing, while we can (and should) use technology to our advantage, we have to keep in mind how it can cause us to expect too much from ourselves (and others). With a little introspection though, we can fight back against the rising tide of ever-increasing expectations for productivity and set realistic goals and deadlines for ourselves. Moreover, we can set a better example for our mentees, the future generation of citizens and scientists, on how to excel without burning out and thrive in this modern world.


Dr. Kate O'Neill is a postdoctoral researcher working at the University of Maryland, College Park and is studying the role of the cytoskeleton in primary neurons and astrocytes.

You can connect with Kate on Twitter at @drkatemon, on LinkedIn, and on ResearchGate.

Further reading:


If you enjoyed this article, why not check out the other resources available on our blog. We are passionate about supporting life scientists at every stage in their careers - from early career life scientists and PhD students to seasoned professors! We support with really low- priced reagents and biochemicals, travel grants, and resources to help with both personal and professional development. We know how tough it is - so we hope you find these helpful!

Advice & guidance for life scientists

Click below to view our essential guides and articles to support life scientists, PhD students & early career life scientists:

Guides for Life Scientists

Help with oral, written and poster scientific presentations

Advice and guidance for life scientists

Wellbeing for scientists

Click below for our resources to help improve your wellbeing:

Wellbeing for scientists

Technical resources

Try our Molarity Calculator: a quick and easy way to calculate the mass, volume or concentration required for making a solution.

Molarity Calculator

Try our Dilution Calculator: an easy way to work out how to dilute stock solutions of known concentrationsDilution Calculator
And - when you get to the stage of planning your experiments, don't forget that we offer a range of agonists, antagonists, inhibitors, activators, antibodies and fluorescent tools at up to half the price of other suppliers - click below to see how we compare with other suppliers:

Save 50% on synaptic signaling tools, GPCR ligands, ion channel modulators, signaling & stem cell tools

Leave your comment