The post-postdoc

The pressures of stagnant research funding, limited academic jobs, and increasing numbers of graduates are creating a bulge in the postdoctoral population cleverly termed “the postdocalypse.” The academic community is addressing this issue – slowly, laboriously, and often reluctantly (see “The case of the disappearing postdocs” below). For the postdoc working on the 5th revision of a manuscript while the grant money runs out, the problem is much more acute.

Understandably, it’s hard for academic scientists to look beyond the current experiment and the next paper. I frequently hear from scientists at the stage of “I’m graduating in a month – now what?” Or, “My postdoc funding is running out – now what?” In the language of entrepreneurship, PhD students and postdocs should be planning an exit strategy.

A knowledge gap big enough to drive a small business into.

Procrastination is a poor strategy for planning a career, but it works as long as there is a next stage. Masters, PhD, postdoc (2nd postdoc)… Those transitions may be difficult, but they occur within the same academic ecosystem. The post-academic transition is something else. The skills, strategies, and tactics are simply different, and this is the knowledge gap that waits at the end of the academic phase. There are many voices bringing visibility to this problem, but let me offer the following as one viewpoint. The market has recognized the difficulty of PhD scientists transitioning to jobs outside academia, and has responded with a small but growing industry: Post-postdoctoral career training. This is the business of training science PhDs and postdocs so that they can begin careers in industry, science policy, or other non-research fields.

There is a harsh way of painting this picture that’s hard to ignore: A decade of scientific education and training does not make you employable. This is a statement that can make postdocs angry, professors defensive, MBAs smug, and university PR firms nervous. But what gets lost is that the career training that most scientists need is not “instead of” their education.

The career development programs I’ve seen have three main offerings: One is to help scientists understand the culture and expectations of industry: for example, putting a priority on teamwork and deadlines. Another is to help grow a professional social network so that more opportunities become available. Finally, there is the process of realizing how many skills are acquired during doctoral education, and which of those a person wants to develop as a profession. The world needs scientists – it just doesn’t need scientists to do the same things they did as grad students and postdocs.

We’ve got procrastination down to a science.

Early-career scientists put off career questions until after the very end of their academic runway. This is largely a matter of urgency. Graduate students are master procrastinators. We finish plotting the data Tuesday morning because the deadline to print a poster is Tuesday at noon. How urgent does preparing for a career feel, when we don’t even know exactly what it is or what that means?

Scientific research is hard. But for grad students and postdocs, at least there is a framework: Advisors, peers, technicians, and instruments are all there to support the research. So it is no small challenge to ask scientists to simultaneously carry out their research and prepare for a career. But the research has milestones and deliverables (experiments and papers). Career preparedness has no milestones and no deliverables; at least none that will be identified by your committee. This is the vacuum that post-postdoctoral career training fills. It gives  a framework for bright scientists, who will solve many types of problems along their academic path, to address a problem they have not thought about.

Expecting universities to deliver combat-ready scientists is a tall order. Those with strong industry collaborations tend to offer more career-development opportunities, but this is not the norm. Some institutions are responding to the needs of graduates with skills training and career workshops, but it’s no surprise that academic institutions tend to focus on academic career training. Professors can be great scientific advisors and still not recognize how important transferable skills, like networking and communication, will be for a non-academic career. This does not show a lack of caring, just a different perspective.

For science PhDs, getting useful data on career outcomes is not easy. Only recently, graduate departments have begun tracking career outcomes of their PhDs, and the data is sparse. Even with data in hand, knowing about career outcomes doesn’t lead directly to career preparedness. Of all the stakeholders in this game, it is grad students and postdocs that have the greatest incentive to look ahead to their career path.

As scientists, we deal in data. Now is the time to treat your career like a research project, even if it’s a small one. How will you go about getting data to prepare for your post-graduate career? Many people are willing to help you: Some are your advisors. Some are strangers. Some do it as a business. Some want to help because they’ve been there. You have the time and resources to prepare for careers you never even knew existed. The only real risk is in not asking the question.

Links

Finding the post-academic career path. A companion article in Lab Without Benches lists post-postdoc training services.

The Case of the Disappearing Postdocs. More scientists are going directly from PhD programs to industry jobs – is the value of postdoctoral training in decline? By Beryl Lieff Benderly, Science, 2015

What a scientist learned from digital analytics

Early in April I found myself at a hotel in Downtown San Francisco, surrounded by experts in the field of internet marketing. I was not lost; I went there to learn how to be a better scientist. Let me explain.

Looking for industry examples of communicating with data led me to digital analytics. This branch of internet marketing relies heavily on data analysis and hypothesis-testing, which sounds like a scientist’s bread and butter.  Like scientists, analysts will be successful if they can demonstrate their approach is better than a gut feeling. Unlike most scientists, digital analysts routinely present quantitative data to non-technical audiences. And being part of  the marketing world, they take their presentations seriously. Continue reading

Who’s that knocking at my door?

or: How I learned to stop worrying
and love LinkedIn endorsements

For scientists looking to break out of academia, nothing is more mysterious than the concept of networking. Wanting to share some insights with my readers, I called up a friend who recently started an MBA program, now immersed in the culture of business. We agreed networking is a critical career skill for scientists, and he mentioned that LinkedIn is especially important in the business community. That’s great, I said – that’s one of the topics I want to write about. Then I gave him my detailed explanation of how people are using LinkedIn endorsements all wrong. Then he started laughing. At me.
Continue reading

What’s your story?

 

As a scientist, your ability to tell a story is as important to your career as knowing how to design experiments. Of all the skills needed to successfully move from academia to industry, good storytelling may be the one that takes the most effort. If good science is the process of obtaining meaningful data, good science communication is using that data to tell a story. This story may be as simple as one chart that clearly shows a cause and effect relationship, or as complex as a scientific journal publication. Continue reading

Let’s bury the Powerpoint Murder Mystery

Jean-Luc Doumont has described some research presentations as mystery stories: The presenter has a result they want to share, but they don’t want to spoil it by telling the audience up front. After a brief introduction to the topic, most of the presentation is spent on methods, experimental details, and data. Finally at the end, they surprise the audience with the results, and wait for the expressions of awe. Consistently, this is never as intriguing as the speaker hoped. While there is growing awareness that scientists need to communicate better, the research presentation is remarkably resistant to change. I’d like to report that among many scientists, the Powerpoint Murder Mystery is alive and well. Continue reading

DIY SOP

 

In the first part of this series I made the case that standardized operating procedures (SOPs), while completely routine in industry, are often missing from academic education. In this essay, I propose a way for you as a university student to not only write a standard procedure, but to make that experience part of your scientific education. The title is a little lighthearted – I don’t intend for anyone to do it all alone. And this isn’t a quick tip or a “lab hack” – it is hard work and it takes time. But considering how much time you’ve spent learning how to do science, it’s also worthwhile to learn how to apply that education where it matters – like in a job. Continue reading

Who cares about standard operating procedures?

Scientists from academia are often puzzled by the emphasis on standard operating procedures (SOPs) in industry. In one of my early R&D jobs, it felt like an obsession – as soon as I got a new result, my managers wanted to know about the process, and whether I had standardized it. I thought it must be due to their background in manufacturing, where everything has to be replicated from one factory to another. But with more experience, I’ve seen this interest in standardized procedures everywhere – manufacturing, R&D, medical devices, pharmaceuticals… everywhere, that is, except the university research lab. For scientists trained to answer questions by designing new experiments, question of process might not make sense, and even seem a waste of time: If standard procedures are so important, how do we explain the many successful research groups that never bother with them?
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Communication: the most important thing you learned to do badly

Most students would be surprised that the term “academic” can have a negative tone in industry. But it’s true – and one place it often gets used is in describing research presentations. For people trained in academia who want to apply their skills to industry, finding a good way to describe their academic experience can be hard. I’m not talking about slide layout or presentation style – I’m talking about the message. The general rule in communication, accepted everywhere outside research institutions, is KISS, for “keep it simple, stupid.” That’s harder than it sounds when you’re surrounded by people who have made their careers by studying complex fields in great detail. One consequence is that you get credibility by describing your work in all its complexity, it great detail. Continue reading