Transferable skills are something I’ve been thinking about a lot this year, as I prepare to leave the familiar yet cruel bosom of Mother Academia. When I first started thinking about what I could do next I came up with… nothing. Zilch. Nada. I know how to do embryonic dissections and make various chemical solutions. What possible good would those skills serve in the “real” world? I was, I concluded, likely unemployable as anything other than a postdoc. But I didn’t want to be a PI. And so I reached the internal conflict that so many postdocs encounter: we are single-mindedly trained for a mythical beast of a position and when we don’t attain that position, be it through choice or otherwise, we have no idea what else we can do.
Rather than fall into a pit of despair I’ve spent much of the last year educating myself about what else is out there and, more importantly, how utterly, awesomely qualified I am for it. Turns out, postdocs are super-employable. Not convinced? Here are Scizzle’s top skills that postdocs can bring to the table:
1) Research skills
There is a whole world of research outside of academia. And it usually pays way better. Whether your skills are clustered at the forefront of molecular biology, all in silico, or more about standing in rivers collecting insects, they will be highly prized by some employer out there. If you want to stay in research, there are many options: biotech, pharmaceutical, medical devices, government, the list goes on. You are very unlikely to be able to continue your exact current project (possibly a relief to some of us), so think laterally about how your skill set is applicable. You currently culture lung epithelium? Great, you are an expert on epithelial cell biology – cosmetic companies would love to have you in their skin lab. Your postdoc was all about the mouse immune system? Pharmaceutical companies would welcome your expertise in developing human monoclonal antibodies.
2) Project management
Postdocs know A LOT about project management; it’s something we do every day. We identify a question and then design a series of experiments to answer it. In planning our experiments we must take into account time, budget, and resources. As the project progresses we must react to failures or unexpected results by designing alternate strategies, again asking do these new plans answer the original question. Once we have data we analyze it and ask whether it answers the question and/or suggests new paths to follow. We often have a set deadline to achieve all this by (paper submission, lab meeting, conference). All in all, postdocs are project management bad asses. In the real world, this translates to being an attractive candidate for jobs as project managers in the pharmaceutical industry and also in many non-research environments.
3) Writing and communication
A common stereotype is that scientists are socially inept bad communicators. On the contrary, postdocs are communication polymaths. When you write a paper or grant you are taking your vast background knowledge and several years’ worth of data, and distilling it down into a concise summary of why the question is important, what you found, and what that means, usually for a reader outside of your niche. If you enjoy this process you may be ideal for employment at a medical communications agency. Perhaps what floats your boat is peer reviewing manuscripts, trying to decide whether a new finding adds to the field, and whether the authors really have shown what they say. If so, an editorial career could be in your future. Or maybe the biggest kick you get is presenting your work at conferences and then talking about it to anyone who’ll listen at the networking session. If you are adept at verbally communicating your science, particularly to a non-expert audience, you could thrive as a Medical Science Liaison (MSL). MSLs are experts in a field who interact with medical and academic professionals on behalf of a pharmaceutical company, conveying knowledge about a product to those involved with it.
4) Broad knowledge of science and the scientific process
If you are interested in science outside of your field – and are a good communicator – you may want to consider a career in science advocacy, policy, or diplomacy. Science advocacy entails relaying what scientists need, often to the government; science policy involves working on both policies that affect science and on how science shapes policies. On a more international scale, science diplomacy involves scientific collaboration between countries to solve a common problem (we’ve already discussed science diplomacy in depth – see here).
5) Ability to quickly assimilate new knowledge
One path taken by ex-postdocs is consultancy. A consultant may one week be asked to provide a solution to dwindling sales of a car, while the next advising a pharmaceutical company on why they should be switching gears to invest in biosimilars. Your postdoc wasn’t on cars or big pharma? Doesn’t matter. The key skill that you have is your ability to research a topic, assimilate the knowledge, critically evaluate it, and come up with new ideas relating to it. This is what consultants do. And they often get paid very handsomely for it.
6) Data analysis
All those hours spent processing and looking for patterns in your data have real-world value. Data scientists are in hot demand across a range of industries. And if you have coding skills to throw into the mix (particularly Python and R) then you’re even more attractive. If not, it’s never too late to learn – pick up Python online at Codecademy and R at DataCamp.
7) A sterling work ethic
NIH salary for a first year postdoc is $42,840, or $823.85 a week. I am not unique in having worked 12 hour days, seven days a week; a first year postdoc doing this will earn $9.81 an hour, a figure above the federal minimum wage ($7.25) but below the median wage at Costco ($13.14). While earning their $9.81 they will push themselves to get a seemingly hopeless experiment to work, all the while eschewing food, sleep, and normal human contact. Then, once the experiment finally fails they will go home to rest, perhaps cry, definitely eat some ice cream, and then come back again the next day to try something new. The capacity of the postdoc to work hard to achieve results on low pay, with little job security, and with no scope for promotion or financial reward is tremendous. Any employer would be lucky to have a postdoc join their ranks – don’t you forget it!
Want to know more about your next move? Do what you know best – research. Attend career panels at your institution, talk to ex-postdocs who’ve moved outside of academia, and set up job searches (for example on LinkedIn or Oystir) based on your skills – just to get an idea of what is out there. Then identify which skills need working on and gain experiences to improve these. An excellent use of your time would be to scoot over to the Independent Development Plan (IDP) website, where you can generate a list of science occupations you are most suited to, based on your answers to an extensive survey of your skills, interests, and values. Your personalized IDP then sets goals for the year, to help you on the way to your ideal career.
Congratulations! You’ve made it to the end of your non-academic job interview! Well, except for that inevitable last question: “Do you have any questions for us?” After an intense period of answering tough questions from the interviewer, it’s your turn to drive the conversation, and for some of us, it’s the scariest part. It’s very important to ask questions, to show you are as interested in learning about the position and the company as they are in learning about you. Not asking questions cuts the conversation short and can be viewed negatively by the interviewer. But your first interview isn’t the time to ask about salary, benefits, dress code, etc. – these questions will be answered when an actual offer is discussed. Instead, you want to ask questions that continue to demonstrate your qualifications for, interest in, and commitment to the position, while providing you with crucial information about the job. So what kind of questions should you ask? Here are a few examples of general questions to get you started:
What do you enjoy most about working with this company? Initiating this conversation will connect you to the interviewer on a more personal level. The answer can also give you insight into company values, as well as an idea about how satisfied employees are with their jobs – if the interviewer struggles to come up with an answer, it could be a red flag about the working conditions.
Can you tell me about the team I will be working with? By asking this question, you are demonstrating your readiness to be a team player. The answer will tell you about the people you will work with on a daily basis and give you an idea about how individuals contribute to accomplishing team goals.
What constitutes success in this position and at this company? This question shows your desire to be successful in the job, and the answer can provide useful information about whether the position is a good fit for you, as well as how to succeed and get ahead in the company.
What skills and experiences would make an ideal candidate? The answer to this question will reveal exactly what the employer is looking for, and can give you the chance to affirm how your background meets those criteria or to discuss how you plan to gain or develop the desired skills.
What is one of the most important challenges currently facing your team, and would I be in a position to help resolve this problem? This question shows you are already thinking about how you can help the company. It also encourages the employer to envision you actually working in the position.
Do you offer continuing education or professional training? This question shows your interest in expanding your knowledge, developing skills beneficial to the job, and growing with the company. The answer may give you an idea as to how new employees are trained, and the value the company places on supporting the professional development of its employees.
What is the next step in this process? This is an essential last question. It shows you are interested in moving the process along. You may also gain insight into how many other candidates are being interviewed, and will get an idea about the timeline, giving you a chance to prepare for the next step.
If possible, it’s a good idea to talk to contacts that have interviewed for or currently hold similar positions to identify questions you can ask that are specific to the job for which you are interviewing. Also, be sure to thoroughly research the company, as it may stimulate relevant questions. Type out a list of your questions and have it easily accessible when the time comes. Having a physical document shows you have put thought and effort into preparing for your interview. It’s also beneficial to practice asking your questions out loud, to ensure you can readily and clearly ask them.
Don’t be afraid of the unavoidable last question! With a little preparation, you can confidently guide the end of the interview to provide useful information about the position, the people, and the company, while simultaneously shining a last bit of light on your stellar qualifications.
Congratulations! You’ve just been asked to interview for the non-academic job of your dreams! Now it’s time to prepare. But an interview outside of academia can be very different from graduate school, postdoc, and faculty position interviews, and after years spent at the bench, it can be difficult to think of your talents and goals outside of the academic box. For a successful interview, it is crucial to talk about your skills, experiences, qualifications, and goals as applicable to the non-academic environment in which you’ll be working. Preparation of answers to some common questions can help you proceed with confidence through the interview discussion. So what kind of questions can you expect? Here are some frequently asked interview questions, with tips for thinking about your answers:
Tell us about your scientific/research background. Be able to explain your research in a clear, concise manner at a level appropriate for the audience. Think about your “elevator speech” – if you only had one or two minutes to explain your research, what would you say? Your answer might be very different if you’re in the elevator with another research scientist versus an accountant, an English teacher, a mechanic, or your grandmother (not joking: I was asked how I would explain my postdoc research to my grandma). Someone from the Human Resources department will likely want a different answer than someone working in a position more directly related to science, so make sure you can give answers accessible to multiple audiences.
Why do you want to leave the bench/academia? For most, the answer to this question is obvious. The challenge is explaining your reasons in a diplomatic manner. “I hate bench research” or “I don’t want to be a PI” may be the simple answers, but what are the deeper reasons for wanting a different career? Perhaps you’re leaving the bench because you feel your strongest scientific talents, like writing or teaching, would be better utilized in a different environment. Maybe you don’t want to be a PI because you want a career that will allow you to spend more time at the bench than many PIs are able. Rather than focus only on what you don’t like about the bench or academia, explain how your strengths and passions are better fit for an alternative career and the position for which you are interviewing.
Why are you interested in [position]? It’s important to emphasize that you are not applying for this position simply because you can’t get a job in or are desperate to leave academia (even if that is the case). What aspects of this career do you think will be most fulfilling for you? How do your talents and background make this position a good fit for you, and vice versa?
What are your strengths/what can you bring to this company? The answer to this question may be more difficult for those applying for non-research positions. As graduate students and postdocs, we don’t often think about the skills we are developing other than the technical skills that make us successful at the bench. Reflect on the non-technical aspects of research at which you excel, and relevant experiences away from the bench. Are you a great writer or a stellar presenter? Have you mentored undergraduate and graduate students in the lab that have gone on to be successful in their own research? Did you design a new assay or come up with a novel approach to solve a difficult research question? Think of specific examples of experiences that demonstrate your expertise in qualities essential or beneficial to the position to which you are applying.
What are you weaknesses? The trick to answering this question is to be honest without being negative. A good suggestion is to frame the negative with a positive on either side. For example, perhaps you have trouble speaking up in large group meetings. You might say something like, “I’m a good listener, which allows me to synthesize the ideas and opinions put forth in a group discussion, but in taking into account everyone else’s comments attentively and in detail, I can forget to or have trouble speaking up and providing my own input. In most cases, however, I am able to find an appropriate time to provide my input to help move the project forward.” But again, be honest – we all have weaknesses, and the interviewers want to see that you can critically evaluate your own performance, so “I don’t have any weaknesses” isn’t an appropriate answer.
How do you handle multiple projects and deadlines? This question should be one of the easiest. As grad students and postdocs, we balance multiple projects all the time. As a grad student, how did you balance classes, studying, and time in the lab? How do you plan for multiple experiments in a day or week to efficiently utilize your time? How do you keep track of multiple research projects? With a bit of reflection, you should be able to come up with some specific examples that show off your time management skills.
After working as an individual/alone, how will you adapt to working on a team? Many people outside of research have the misconception that scientists work alone, isolated from others at the bench, mired in their own projects. It’s important to (kindly) dissolve this stereotype. Scientists collaborate within their labs, their departments, their institutions, and with outside institutions. We participate in lab meetings, seminars, and conferences to get feedback on our research and provide insight and ideas to others. Discuss with the interviewers your experiences working with other scientists and how these experiences have prepared you for working in a team-oriented environment.
Where do you see yourself in 5 years/what are your long-term career goals? Your answer to this question should show your enthusiasm for the position and suggest your commitment to growing and developing your career with the company. Why is this position a good next step for you? What skills are you hoping to develop and what experiences are you hoping to gain? You might express interest in taking on management responsibilities or getting involved in certain areas or projects. Show motivation and realistic ambition in this career path.
It’s beneficial to talk to other people who have recently applied or currently work in jobs similar to the position you are applying for to get an idea of potential questions specific to the position. Take some time to really reflect on your answers to come up with specific, concise, and sincere answers. Most importantly, practice answering these questions out loud, perhaps with people from a variety of backgrounds – a coworker, a scientist from a different field, someone who works in the career you are pursuing, your grandmother – to ensure you can quickly and efficiently verbalize your thoughts. With preparation and practice, you can ace your non-academic interview and get the job to put you on your way to a fulfilling career.
Academic science is traditionally built on an apprenticeship model, in which a student works under the mentorship of a principal investigator, learning the skills of the trade and preparing to be an independent researcher. After a few years of training as a post-doctoral fellow, a scientist would likely obtain a tenure-track position at a university (if choosing the academic route) and mentor the next generation of scientists, continuing the academic circle of life. In the past few decades, this situation has drastically changed.
As most graduate students and post-docs have probably noticed, there has been an enormous amount of discussion on the difficulties of landing a good academic job following the PhD. In searching for the causes of this phenomenon, commentators have described several factors, two of the most salient being the recent stagnation in NIH funding (adjusted for inflation), and a dramatic increase in the number of PhDs awarded in the natural sciences. To provide context for the situation in the U.S., in the past three decades about 800,000 PhDs were awarded in science and engineering fields, compared to ~100,000 tenure-track positions created in the same time frame. These forces have changed the structure of the scientific academy, the result being a new arena in which many PhDs are competing for a smaller number of academic jobs, and with those who land one often shuttling between low-paying adjunct positions with meager benefits and no possibility of tenure.
Economists studying the U.S. scientific academy, particularly the post-doctoral fellow system, have gone so far as to describe it as a “pyramid scheme.” This type of financial scheme operates by luring new investors with the promise of an easy payout; but the players nearer the top profit the most, at the expense of those at the bottom.
Post-doctoral fellows, often the main workhorse of a biology research lab, are cheap (~$40,000 starting salary in U.S.) and replaceable, owing to the large excess of PhDs on the market; graduate students are even cheaper, as they often teach to earn their salaries. And a principal investigator (PI) running a large, well-funded lab will gain status and prestige for all grants and publications generated by their personnel.
Despite the less than ideal job prospects awaiting science PhDs, the government and media continue to strongly advocate education in the STEM fields, encouraging more undergraduates to pursue STEM majors and thereby increasing the number at the graduate level. While U.S. society’s general enthusiasm and respect for science is definitely positive, it is irresponsible to push so many young people into this career path without making substantial funding commitments. Certainly, not all PhD students intend to pursue a career in academia, and those who do may later find that their passion lies elsewhere, for instance in a biotechnology field. However, one should keep in mind that the past decade has also been rough for the U.S. pharmaceutical industry. Since 2000, thousands of U.S. and European industry research positions have been lost, while several “big pharma” firms plan to open new R&D centers in Asia, where costs are lower.
Although the outlook might seem bleak for those currently navigating these turbulent academic waters, the calls of post-doctoral advocacy organizations for increased salaries and benefits may finally be making a difference. This year, the NIH increased the base salary of its National Research Service Award post-doctoral trainees, and other institutions have increased post-doctoral pay and benefits, resulting in higher post-doc satisfaction.
These proposals will not only increase the quality of life for current post-docs, but also change the incentive structure of the marketplace: as laboratory personnel become more expensive, PIs will hire more selectively. Fewer PhDs will enter the post-doctoral route, either opting to pursue a career in industry or another field entirely. It may take years for these policy changes to be fully implemented, but hopefully academic scientists will be able to pursue their passion without fearing for their livelihoods or career prospects.
You did it! You finished all your coursework, successfully presented and defended your thesis proposal, and are now officially a PhD candidate! You’re probably tired but relieved to have finished your qualifying exam, and excited to get started on those experiments you proposed. Better get working so you can stick to that timeline, find some novel and interesting data to publish, and be able to graduate in 3.5 more years right? Let me offer a few words of advice as you get ready to start your third year.
First, add at least 6 months to those proposed dates on that timeline. Your PI is right, they are overly optimistic, and even the most straightforward-sounding experiments will take longer to troubleshoot and optimize than you think.
While you’re troubleshooting and optimizing, talk to people. Talk to labmates or colleagues in other labs who may have experience with your procedure. Reach out to the technical support staff at the companies producing your reagents. If for whatever reason you think your yield from commercial kits is not as high as expected, and even if you have scoured their websites without finding anything useful, call technical support and they might be able to give you some tweaks that will make all the difference.
I’m not going to lie, third year is going to be tough. You will go months without seeing any positive data. You will have some promising results, and then fail to be able to reproduce them. In the spring, when it’s time to submit poster abstracts to the department retreat and to the big annual conference, you will remember that time in second year when you remarked to your friends, “Next year I’ll have data to present!” and you will wonder where you went wrong.
This year, some of your classmates will leave with their Master’s degree and pursue other career paths, and you’ll wonder whether you should do the same. Take the time to look at job postings and attend career panels. Again, talk to people. Learn about what is out there, see what types of jobs interest you and find out what skills are needed for those positions. Maybe it will make more sense to leave with the Master’s degree, or maybe not. Maybe you will need to learn new skills; make a plan and figure out how to best acquire and demonstrate those skills (i.e. online or in-person classes, volunteering, etc.)
Cultivate your life outside the lab. Yes you will spend many hours working in the lab, but make sure you step away from the bench to get some fresh air. Connect with your classmates and commiserate over the struggles of grad school. Find some hobbies, maybe a local recreational sports league, or some fitness classes. Get out into nature (fun fact, a recent PNAS study has suggested that nature walks may help calm the brain. Take care of yourself so that you can go into lab rested and recharged.
Things will get better. You may need to switch gears and try different approaches and techniques to get at the same question. While you don’t want to juggle too many experiments and projects simultaneously, it might also not be ideal to focus solely on one single experiment, so try and find some balance. Having multiple experiments increases your chance of finding something that works, but you don’t want to split your time and attention too much.
Make sure you take time to read. You will be reading anyway as you troubleshoot, trying to see what conditions other people have published successfully, but take some time to read other papers relating to your project, your field, or just science in general. Step back and think about how your experiments fit into the bigger picture. Read about new discoveries and remind yourself why you were so excited about your project in the first place, and why you are in science to begin with. Remember, grad school is a marathon, not a sprint.
Measuring the value of science has always been – and, likely, will always remain – a challenge. However, this task, with regard to federal funding via grants, has become increasingly more daunting as the number of biomedical researchers has grown substantially and the available funds contracted. As a result of this anti-correlation, funding rates for NIH grants, most notably, the R01, have dropped precipitously. The most troubling consequences of the current funding environment are (1) the concentration of government funds in the hands of older, established investigators at the cost of young researchers, (2) a shift in the focus of lab-heads toward securing sufficient funds to conduct research, rather than the research itself and (3) an expectation for substantial output, increasing the demands for preliminary experiments and discouraging the proposal of high-risk, high-reward projects. The federal grant system has a direct impact on how science is conducted and, in its current form, restricts intellectual freedom and creativity, promoting instead guaranteed, but incremental, scientific progress.
History has taught us that hindsight is the only reliable means of judging the importance of science. It was sixteen years after the death of Gregor Mendel – and thirty-five years after his seminal publication – before researchers acknowledged his work on genetic inheritance. The rapid advance of HIV research in the 1980s was made possible by years of retroviral research that occurred decades prior. Thus, to know the value of research prior, or even a handful of years after publication, is extremely difficult, if not impossible. Nonetheless, science is an innately forward-thinking endeavor and, as a nation, we must do our best to fairly distribute available government funds to the most promising research endeavors, while ensuring that creativity is not stifled. At the heart of this task lies a much more fundamental question – what is the best way to predict the value of scientific research?
In a paper published last month in Cell, Ronald Germain joins the conversation of grant reform and tackles this question by proposing a new NIH funding system that shifts the focus from project-oriented to investigator-oriented grants. He builds his new system on the notion that the track record of a scientist is the best predictor of future success and research value. By switching to a granting mechanism similar to privately funded groups like the HHMI, he asserts, the government can distribute funds more evenly, as well as free up time and space for creativity in research. Under the new plan, funding for new investigators would be directly tied to securing a faculty position by providing universities “block grants,” which are distributed to new hires. In parallel, individual grants for established investigators would be merged into one (or a few) grant(s), covering a wider range of research avenues. For both new and established investigators, the funding cycle would be increased to 5-7 years and – the most significant departure from the current system – grant renewal dependent primarily on a retrospective analysis of work completed during the prior years. The foundation for the proposed granting system relies on the assumption that past performance, with regard to output, predicts future performance. As Germain remarks, most established lab-heads trust a CV over a grant proposal when making funding decisions; but it is exactly this component of the proposal – of our current academic culture – that warrants a more in-depth discussion.
Germain is not the first to call into question the reliability of current NIH peer reviews. As he points out, funding decisions for project-oriented grants are greatly influenced by the inclusion of considerable preliminary data, as well as form and structure over content. Others go further and argue that the peer review process is only capable of weeding out bad proposals, but fails at accurately ranking the good. This conclusion is supported by studies, which establish a correlation between prior publication, not peer review score, and research outcome. (It should be noted that a recent study following the outcomes of greater than 100,000 funded R01 grants found that peer review scores are predictive of grant outcome, even when controlling for the effects of institute and investigator. The contradictory results of these two studies cannot yet be explained, though anecdotal evidence falls heavily in support of the former conclusions.)
Publication decisions are not without biases. Journals are businesses and, as such, benefit from publishing headline-grabbing science, creating an unintended bias against less trendy, but high quality, work. The more prestigious the journal, the higher its impact factor, the more this pressure seems to come into play. Further, just as there is a necessary skill set associated with successful grant writing that goes beyond the scientific ideas, publication success depends on more factors than the research itself. An element of “story-telling” can make research much more appealing; and human perception of the work during peer review can easily be influenced by name recognition of the investigator and/or institute. I think it is time to ask ourselves if past publication record is truly predictive of future potential, or, if it simply eases the way to additional papers.
In our modern academic culture, the quality of research and of scientists is often judged by quantitative measures that, at times, can mask true potential. Productivity, as measured by the number of papers published in a given period of time, is a standard gaining momentum in recent years to serve as a meaningful evaluation of the quality of a scientist. As Germain states, a “highly competent investigator” is unlikely “to fail to produce enough … to warrant a ‘passing grade’.” The interchangeability of competence and output has been taken to such extremes that pioneering physicist and Nobel Prize winner, Peter Higgs, has publicly stated that he would be overlooked in current academia because of the requirement to “keep churning out papers.” The demand for rapid productivity and high impact factor has caused an increase in the publication of poorly validated findings, as well as in retraction rates due to scientific misconduct. The metrics used currently to value science are just as, if not more, dangerous to the progress of science as the restrictions placed on research by current funding mechanisms.
I certainly do not have a fail-proof plan to fix the current funding problems; I don’t think anyone does. But, I do think that we need to look at grant reform in the context of the larger issues plaguing biomedical sciences. As a group of people who have chosen a line of work founded in doing/discovering/inventing the impossible, we have taken the easy way out when approached with measuring the value of research. Without the aid of hindsight, this task will never be objective and assigning quantitative measures like impact factor, productivity, and the h-index has proven only to generate greater bias in the system. We must embrace the subjectivity present in our review of scientific ideas while remaining careful not to vandalize scientific progress with bias. Measures to bring greater anonymity to the grant review process and greater emphasis on qualitative and descriptive assessments of past work and future ideas will help lessen the influence of human bias and make funding more fair. As our culture stands, a retrospective review process, as Germain proposes, with a focus on output runs the risk of adopting into the grant review process our flawed, and highly politicized, methods of judging the quality of science. I caution that in parallel to grant reform, we begin to initiate change in the metrics we use to measure the value of science.
Though NIH funding-related problems and the other systemic flaws of our culture seem at an all time high right now, the number of publications addressing these issues has also increased, especially in recent years. Now, more than ever, scientists at all stages recognize the immediacy of the problems and are engaging in conversations both in-person and online to brainstorm potential solutions. A new website serves as a forum for all interested to join the discussion and contribute reform ideas – grant, or otherwise. With enough ideas and pilot experiments from the NIH we can ensure that the best science is funded and conducted. Onward and upward!
This is the second in a series of posts by former recruiters and co-founders of Oystir, a new free service helping STEM PhDs find non-academic jobs.
In our last post, we laid out the basics of how to write a winning resume. Today, we discuss what we have found to be the most impactful part of a resume, and the one most PhDs leave off: the executive summary.
An executive summary is a short statement at the top of your resume that quickly summarizes what makes you the right candidate for the job. We recommend 3-5 punchy sentences (more on what they should say later) that emphasize your most relevant strengths and experiences and make the best case for why you are uniquely qualified for the job. In this post, we’ll cover why you need an executive summary and how to get started writing one.
Why do you need an executive summary?
1) Quickly articulates your value – “the elevator pitch”
Imagine you were in an elevator for 30 seconds with the hiring manager. What would you say to convince them to hire you? That is your “elevator pitch.” This is the purpose of your executive summary. We recruiters love it. As a hiring manager, I can read 3-5 sentences and know if you’re qualified. You save me time and effort. The great benefit for candidates is that you control your story and get to make the case why you’re a great candidate, instead of relying on my interpretation of your history of experiences.
The first thing recruiters see is what is up-front and center. This is also the section they will spend the most time on. So it is crucial you put the most important information they need to see up front in an executive summary.
From the beginning, list the most important pieces of information that demonstrate how you are uniquely qualified for the job. This will hook the hiring manager and make them want to read more about you.
Consider the two example resumes below (name and institutions have been changed). They are both the same person – a postdoc applying for a scientist job that requires experience with CRISPR/Cas9 technology, leadership and management. In the version with an executive summary, the candidate quickly summarizes his background as an accomplished molecular biologist with major publications, then highlights his experience CRISPR/Cas9, and emphasizes evidence of his ability to manage (mentoring students) and lead (co-founding a program). In the version without an executive summary, the recruiter doesn’t get any of that color. Worse still, by leading with education instead of experience, the recruiter has to get past the first third of the page to see if the person has any gene editing experience or has demonstrated leadership or management. You took 2 of the 7 seconds I was going to spend on your resume and wasted it with low-value information.
2) Makes you stand out from the crowd: Emphasizes strengths and highlights transferable skills
When you apply for a job, your resume will likely be one of a long stack under review. It is essential that you stand out from others and don’t blend into the crowd. By leading with your education or your postdoc, you make it difficult for the recruiter to identify how you are different than anyone else – there are a lot of PhDs. Make that job easier for them by making your relevant skills and experiences pop out at them up front in an executive summary. Recruiters will thank you for not making them go digging through your resume to figure out what makes you qualified and different from other PhDs.
This is especially important if you are applying to an industry job from academia. Many jobs list industry experience but recruiters ultimately consider applicants without it. Leading with an executive summary gives you have time to persuade a recruiter you’re worth considering, rather than emphasizing the fact you are fresh out of academia. Executive summaries are also helpful if you are applying for a role that doesn’t traditionally get filled by PhDs; you get a few lines to emphasize your transferable skills and convince the hiring manager why you should be the exception.
In addition to highlighting your skills, an executive summary conveys the important message to recruiters that you are a strong communicator. Most industry jobs will require you to synthesize complex concepts into a few key takeaways and communicate them clearly and concisely. By crystallizing your experiences into several punchy bullet points, you will demonstrate you have the communication skills to craft a narrative. If you can sell yourself, you can sell a company’s product.
3) Targets a specific job and aligns you with employer needs
Traditionally, people kicked off their resumes with an “objective statement,” in which they wrote what they were looking for. You may have seen objective statements like this before:
“Seeking to obtain a research scientist position at a leading biopharmaceutical company.”
“OBJECTIVE: To apply expertise in molecular biology and bioinformatics in a fast-paced challenging environment.”
Objective statements are essentially useless – you’re telling me you want to apply for the job you have applied for. I know that. Ditch the objective statement for an executive summary.
The major problem with objective statements is they tell hiring managers what they already know. If you’re applying for a research scientist job, the employer knows your objective. That’s why you sent them your resume. Don’t waste precious space in your resume telling them what they know.
Additionally, objective statements are written with your goals in mind, not the hiring manager’s. Hiring managers are looking for what you will bring to the job, not what you want to get out of it. You wouldn’t try to sell your house by saying you need the money; you’d take the buyer’s perspective and show off what they’d get by purchasing the house. On your resume, take the employer’s perspective, understand their needs and demonstrate how you would fulfill them.
So how do you get started writing your executive summary?
1) Identify the employer’s needs and how you fulfill them
Just as your resume should be tailored to the job for which you are applying, so should your executive summary. In fact, it is even more crucial to tailor your summary since that is the one part the recruiter is guaranteed to read.
Read the job description to determine what is most important: If it’s a research scientist role, what lab techniques are they looking for? If it’s a data analyst role, what scripting languages are they looking for? If it’s a consulting role, are they looking for entrepreneurial experiences? Is it important to emphasize your experience managing others or should you emphasize your written communications skills?
Once you’ve identified what skills the job needs, go through your resume to identify which of those skills you have. List the most relevant experiences that pertain to each skill set. Of the scientific research techniques listed in the job description, which have you mastered? If the position requires you to lead a team, when have you managed others? If the job requires you to be part of a new unit, have you started an organization to prove you’re a leader who can shape it? If it requires communication skills, have you written articles for popular consumption or given presentations to wide audiences?
2) Understand it’s YOUR story
In addition to tailoring your summary to jobs you apply for, make sure your summary is tailored to YOU. We realize that sounds a bit obvious, but often we read resumes whose opening sentence is something like:
“Highly motivated scientist with strong problem-solving skills, tireless work ethic and detail-oriented mindset.”
That could describe just about any PhD applying to any job. Throughout your executive summary and resume, try to emphasize skills, experiences and attributes unique to you. When you write a bullet point, ask yourself, “Could just about anyone say this?” If the answer is yes, rewrite.
3) Write the bullet points
Now that you’ve done some initial thinking about what skills and experiences you have that are relevant to the job and make you stand out, it’s time to put them on paper.
Your executive summary should appear right below your contact information and be about 4-8 lines. We prefer bullet points to paragraph form: a big block of text is intimidating to read and difficult to skim, which frustrates hiring managers. This is more important for bullet points under your experience section, which we will cover more in another post, but the rule applies to the executive summary as well.
Here’s a rough outline for your executive summary:
Bullet 1 – The Pitch
Summarize yourself in a sentence (e.g., “Creative biochemist with demonstrated leadership skills and 7 years experience in immunology and cancer biology research”)
Bullets 2-3 – The Skills
Emphasize the most relevant skills you have tailored to the job description (e.g., “Deep expertise in mathematical modeling in monte carlo simulations, performing numerical analysis on large data sets and data visualization”)
Bullets 4-5 – The Fit
Highlight your soft skills and anything else impressive that defines you (e.g., “Former professional poker player well-prepared for an environment of rapid decision-making and financial risk”)
To get started on your executive summary, here are some questions to ask yourself to help flesh out each bullet point:
For inspiration, here are a few executive summaries of real PhDs we have helped get jobs (names changed of course). Notice how the emphasis changes depending on the job they apply for!
This was one of a series of posts on winning resume strategies for PhDs. Stay tuned to Scizzle for future pieces including making your skills and achievements stand out from the crowd and samples of “before” and “after” resume success stories.
Rudy Bellani and Zach Marks are co-founders of Oystir, a new free service helping PhDs find non-academic jobs. You can reach them at email@example.com. To begin exploring what jobs match your skills, sign up at www.oystir.com.
It is a common conversation topic among researchers, but it was not until the NPR article saw the light, and the dark side, that the public realized the problems that young scientists are facing when pursuing a successful career in Academia. As we raise awareness about these tribulations, my colleagues mentioned how a “postdoc”’s quality life depends on the quality of the lab, the institution, the project, the relationships with colleagues and the Principal investigator or PI (the boss), not forgetting that this is a very self driven career. So, if your hypothesis is very difficult to prove, or you have been hitting your head against the wall with all the negative results that took you years to get, you may eventually come to hating this path and leaving Academia. The same if you have been working in a non “hot field” where the funding sources do not consider interesting enough to support or your PI is not supportive, or you have a very wicked competence inside or outside the lab. All these negative situations can aggravate the perspective of the very little options one may have by pursuing a career in Academia. On the other hand, if you are obtaining excellent results, publishing in top tier journals, made hundreds of good connections and collaborators, have a “great boss” and literally love you job… well, probably you are also doomed…
One solution could be implementing the business approach to the scientific mindset: Why only having one PI per lab? At the end, two minds think more than 1. Perhaps collaborative research centers have a solution were 2 or more PIs can have access to more equipment, grants and professionals, and therefore use the best skills needed for the job, like a company where you have an executive committee and you distribute the stock between the employees, in order to make them be part of the enterprise.
Having a business mindset would mean to have a planed strategy about your career development. Having a backup career plan is one example of this: starting to apply for jobs before needed, or before it is too late. Begin with your preparation to be a leader, and make your PI know, and discuss a good starting point. Look for leadership opportunities in any situations, such as coordinating workshops or conferences.
Sign up to run workshops and career developing series!. Many postdocs can discover a great professional gain if these opportunities would be offer to them. Get training in other expertise to be competitive in, for example, the investing or consulting field. Taking classes about how to give a class is a great example of a course that could be offered to postdocs and graduate students, in order to train them to explain and transfer their empirical knowledge to the next generation.
A month ago, at the Mount Sinai Postdoc symposium, Dr. Bruce Alberts (yes, THE Alberts, from “The Molecular Biology of the Cell” book) who spoke about “The Future of Biology: Keeping Science Healthy” and illustrated the dramatic changes in the age of the scientist successfully obtaining project grants from NIH. In contrast to 30 years ago, the average age of new investigators with PhD at initial RO1 was 36.8 year old, a large number of grants were awarded to scientist in their early 30s, but this tendency has been decreasing drastically, to the point where now, the mean age for receiving these prestigious grants is 42 years of age. Dr. Alberts, himself, made fun on the fact that he obtained his postdoc position, before been awarded with his PhD. (which actually his thesis was rejected the first time, delaying the whole process) and learned from his failures. He also pointed out that he got his professor position at a very young age, something that is almost impossible nowadays. He advocated for a change in this unfair situation, which cripples the young innovators from getting a start. Also, he encouraged researchers to get out of the lab and talk to the public about science and its importance. First, to attract/engage curious minds to the scientific field, and second to communicate “in simple language” what we do for 9 hours plus per day in the lab.
We must offer to all this new scientific minds the reality about the current situation of science, but we also need to fix it, so it is not going to turn into a snow ball and make disappear all the interest in pursuing a scientific career for the new generations. In a business mind-set we must recognize that the money is not only in the governmental funding, but also in private foundations and other organizations like angels or venture capitals. So go out there and try to pitch your science to investors.
In many ways, graduate school is a lot like Disney’s Beauty and the Beast. Belle, an intelligent girl with her “nose stuck in a book,” seeks to escape her small, provincial life and adventure to “the great wide somewhere” (wherever that may be). Along her journey, she becomes imprisoned in a castle governed by the fearsome Beast, exudes patience and compassion in the face of seemingly insurmountable challenges, and catalyzes the transformation of her once nemesis into a benevolent, more universally accepted form. The parallels should be obvious: You are Belle. Graduate school is the castle. Beast is your thesis. (And that patience/compassion part is just Disney magic.)
Pursuing a PhD is jarringly different than undergraduate education, industry jobs, or the like. First of all, you won’t know anything. Literally. That’s kind of the whole point. You will wade into a project in which the unknown is your only foundation, much like flailing for the bathroom light switch in the middle of the night (you know it’s there, but you just can’t find it); you will become a connoisseur of seminar cuisine (cookies, stale crackers, room-temperature cubes of cheese, more cookies, and pizza); and vacations will become confused for the term “conference.” One could argue a conference is just an evolved species of a vacation, but alas, I’m not an evolutionary ecologist.
So how does one embrace this flood of change with all the patience and compassion of a Disney protagonist? Here are some tips to get you started:
As many will attest, graduate school levels the playing field. You may have been at the top of your class as an undergraduate, but so too are your next-door neighbors. But really, who cares? There is no longer a fight to be the best; there is only the fight to do your best. Science demands humility as you stumble for ways to find the answers to exceedingly difficult, nearly impossible questions. Being ignorant is innate to the job description: If you already knew something, then why study it? The excitement lies in what we do not know. Learn to say “I don’t know” with care and confidence. Admit it, embrace it.
The first year of graduate school is incredibly demanding. You must balance challenging rotations, difficult classes, and unfamiliar environments. When things get difficult, remember this: You are here for a reason. People had enough confidence in you to pay you to study what you love. While you may not find confidence in yourself, know that others have already found it for you. You can do this.
You will be tempted to compare your achievements to those of your classmates. This can snowball throughout your graduate education. “He got an A on the test, but I got a D…I must be stupid.” “She completed her qualifying exam before I did! I’m so behind!” “She got a grant, why didn’t I?” “He already has four publications…I’ll be lucky if I get on a review!” This can become an all-consuming process, but here’s a tip: Just stop. Never, ever compare yourself to that of a colleague. Sure, comparison is healthy from time to time, but as soon as you start trying to correlate your achievements (or lack thereof) with those of a peer, things quickly go south. Every person comes from a different life, educational, research, and mentorship background. Making a comparison in this scenario is pointless because the comparisons will never be equitable. Don’t worry about how Sally or Sean got what you wanted a step faster. Do your own thing. Do you.
Manage your time
This may be self-evident, but as you start juggling all of your responsibilities, you may find yourself saying, “Oh, wow, it’s 4 AM, and I forgot to eat today!” Don’t be this person. Budget time to complete your classwork, execute in rotations, an—of course—eat! If you aren’t sure you are performing well, seek advice from a fellow student, tutor, or advisor. No one wants to see you fail. Everyone wants to see you succeed.
…A lot. Reading scientific articles is one of the most important yet underdeveloped skills a graduate student possesses. To help get you started, try this: For every figure, write out the question being asked, the experiments that answer the question, the results of those experiments, and how those results feed into the overarching message of the work. You’ll ace discussions, and reading will become faster and second nature. And of course, if you haven’t already, sign up for Scizzle to keep up with your scientific interests and field.
Be happy, be healthy
(Not to quote Cheerios, but it is sound advice). Being healthy is a mental process as much as it is a physical one. Exercise, eat well, and play. Develop a close circle of friends you can lean on in times of need. Go see a movie. Take a weekend trip outside your campus. Relax and build time for yourself. You cannot perform your duties as a graduate student (or anything, really) if you are miserable and ailing. Take care of yourself first so you can be your best version every day. If on some days you can’t remember what that version is, then please, channel your inner-Belle. Be curious, courageous, and open to change. Steer clear of Gastons. Tame the Beast.