Launching a nonresearch career doesn’t mean leaving behind everything you learned as a scientist. The skills you developed as you dove into your projects and communicated your results are valuable in many jobs. If you’re not convinced, read on for some specific examples of how Ph.D.-holders put their skills to use outside the lab.
Learning new fields
Kenneth Gibbs Jr., Program director in the Division of Training, Workforce Development, and Diversity at the National Institute of General Medical Sciences
Learning new fields is a skill I developed in graduate school that I continue to use now as I manage research grants in scientific areas that are outside my previous expertise. When I was a graduate student, I was very interested in stem cells and the signals that regulate them. At the time I didn't have a background in the topic, so I had to read lots of literature—where I encountered unfamiliar terms—to orient myself to the field, and then I would identify knowledgeable people to talk with to refine my ideas. When I transitioned into policy research, I was very interested in understanding the factors that influence the career development of Ph.D. students and postdocs, and how they differ across race/ethnicity and gender. Again, this meant burying myself in the relevant literature, where again I found myself wrestling with unfamiliar terminology, and then identifying people to talk with. The area of study changed, but the process did not.
Critical in this process was learning to ask for help. Sometimes we fear appearing uninformed if we ask questions, and this fear can be especially pronounced if you're part of a group that's been historically excluded or marginalized. As a black man in science, I have felt—and in some ways continue to feel—this acutely. However, it is important to overcome this fear and ask for the help you need. It saves you lots of time and helps you be more productive. I've found over and over again that people are usually willing to help if I ask.
Christopher Stern, Life sciences consultant at L.E.K. Consulting
My graduate program and scientific mentors during my Ph.D. and postdoc emphasized communication as a critical skill, in research and beyond. The scientific community values elegant experiments and transformative results only when they are communicated effectively. In grant applications, researchers must clearly articulate the rationale and plans for future experiments. In peer-reviewed manuscripts and during presentations, they must effectively summarize data to introduce new hypotheses and results to their colleagues. As a strategy consultant, written and verbal communication is still at the core of what I do every day, but the tools and flavor differ. PowerPoint is the go-to medium at L.E.K. to communicate our approach, results, and recommendations. We constantly strive to “write slides” that strike a balance between brevity and thoroughness. Concise verbal communication has outsized importance given the rapid pace of consulting work, crunched timelines, and busy colleagues. My team may have a 1-hour meeting to support our perspective on a critical client decision with multimillion- or billion-dollar implications, or I may have 2 minutes in an elevator to convince a managing director of the merits of a particular analytical approach. In this job, success hinges on clear, concise, and convincing verbal communication.
Sheila Cherry, President and senior editor at Fresh Eyes Editing
During my postdoctoral training, I found that I needed to do a better job allocating my time so that I could accomplish both short- and long-term tasks. I developed a habit of starting my day by recording each task or step in a task that I needed to achieve that day, and then mapping out the day to maximize my time. For example, I might get an experiment started before heading off to check my research animals and get back to the bench to start the next experiment before attending a seminar. Now, as the owner of an editing business, which requires that I wear more—and more varied—hats (editor, supervisor, customer service rep, marketer, writer, teacher, bookkeeper), it is more critical than ever for me to guard my time carefully to maintain my productivity. I still make a list in the morning of what I need to accomplish for the day and week ahead. Beyond this, I prioritize two or three tasks that must be done before I can check or respond to emails or voicemails. (I recently added a note to my email signature indicating that I respond only during certain times of the day.) It is easy to get bogged down in emails, and this approach keeps me from squandering my most productive times of day (particularly after morning coffee) on tasks that require less output.
Tackling complex topics
Jennifer Reininga-Craven, Associate director of research development at Duke University School of Medicine
The ability to conceptualize complex problems—including breaking down and building up complicated concepts from their fundamental elements and posing a range of reasonable solutions—has served me well, both when I planned experiments as a genetics trainee and now when I edit grants as a research development professional. As a postdoc, when I was developing a protocol to investigate variations in yeast phenotypes in a new experimental environment, I first needed to identify how subtle changes in experimental design—such as cell density, experiment length, and culture age—interacted to influence phenotypes. Then, I was able to use this information to design experiments that revealed interesting results that might have otherwise gone unnoticed. Now, when I edit grants, I first aim to broadly understand the area of study, and then I work to identify the specific elements that provide the strongest rationale for the proposed study. After doing so, I can help investigators sharpen their logic by, for instance, suggesting information they should add to justify their proposed research activities more convincingly or identifying red herrings (arguments that are not centrally relevant to the grant topic and may confuse the reviewer).
Connecting to diverse audiences
Kyle Nakamura, Field application scientist at Illumina
As a field applications scientist, I work with customers of every disposition, temperament, background, and experience level imaginable, sometimes all in the same room at the same time. I’m able to do that because I had a breadth of experiences adapting my communication style to a wide range of different audiences. In grad school, I took every opportunity to work on my communication skills: I taught new students, participated in inter-institutional research group meetings, helped with academic recruitment, and assisted with some departmental activities. As a postdoc, I helped build a core facility and worked with academic customers across a variety of disciplines. I also spent a lot of time working on my communication skills outside of academia. I mentored martial arts students; volunteered extensively with diverse groups, including at-risk youth and convicted felons at the state penitentiary; and participated in several types of outreach and peer-counseling. For Ph.D. candidates and postdocs needing more communications practice, I would strongly recommend getting out of your silos and looking for opportunities both inside and outside of academia.
As a researcher, you develop the ability to look around you, identify a problem, ask the right questions, and then collect appropriate data to guide the development of solutions. Even though I’ve been out of the biomedical research lab for 7 years, I still regularly use many of these skills in my work running educational programs geared toward improving equity and inclusion in the sciences, as well as connecting scientific research with the public. With limited time and resources, it’s important to make sure our efforts are actually achieving the goals we set out to meet. Assessing educational programs is not that different than doing research in the lab. You identify a problem, which is your rationale for why the program is a good use of time and resources. You hypothesize why and how the program will have an impact. You think about what data are most appropriate for assessing your hypothesis and the best way to collect it. Then you analyze all those data and make adjustments to your program based on the results. Having been a laboratory scientist for almost a decade before entering my current position, these data collection and assessment portions were second nature.