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Reflections Blog

Post-Ph.D. Career Plans: Consider the Possibilities

3/7/2020

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Ph.D. Career Trends
The post originally appeared on PassioInventa, a site run by graduate students to serve as a platform for science communication. 
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Many people assume Ph.D.-trained individuals work in two predominant areas: academia or industry. Most professors have Ph.D.s, and academic careers are  considered to be the “default” or even preferred path during one’s graduate training.
The other major career bucket Ph.D.s fall into after their training is industry. What do we mean by “industry”, though? Many assume an industry Ph.D. works in pharmaceutical development or some other research and development (R&D) role, and some, indeed, do. However, there are so many additional roles Ph.D.s can fill in industry as well as in government, nonprofits, and academia that don’t fall into the neat buckets of academic or industry scientist.
What do Ph.D.s do for work? Let’s look at the data.
A wealth of career data for Ph.D. recipients is collected by the National Science Foundation (NSF) in its
Survey of Earned Doctorates (SED) and Survey of Doctorate Recipients (SDR). The SED focuses on recent Ph.D. graduates each year (Table 1) while the SDR captures employment information of individuals with Ph.D.s in science, engineering, or health fields, regardless of when they received their degree (Table 2).
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Table 1: Survey of Earned Doctorates (SED) data on primary work role for 2018 Ph.D. graduates in the life sciences, physical/earth sciences, and engineering. R&D, Research & Development
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Table 2: Survey of Doctoral Recipients (SDR) showing primary work role of individuals with life sciences, physical/earth sciences, or engineering degrees in 2017. R&D, Research & Development
The data collected by the NSF demonstrate that anywhere from 34.1% to 37.3% of science/engineering doctorates ultimately perform work beyond R&D and teaching (Table 2, Something Else column). That number might surprise current graduate students and postdoctoral trainees who often consider their career options limited.  
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Ph.D. employment trends are changing: The elephant in the room 
A great challenge in graduate education and career/professional development is ensuring Ph.D.-trained researchers understand that the “traditional path” of securing a faculty position is becoming more difficult to follow. This trend was  summed up well by Schillebeeckx et al 2013 (reproduced below), who show that the cumulative number of Ph.D.s awarded in Science & Engineering fields has grown rapidly compared to available faculty positions over the past few decades.
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This  chart includes data collected through 2011; the startling trend has unfortunately continued. More recent data can be accessed from the SDR & SED on employment trends for Ph.D.-trained scientists and these data continue to show the decline in the percentage of Ph.D.s working in tenure-track faculty positions. The trend is most apparent in the SDR data where employment in academic positions is broken down by tenured faculty, those on the tenure track, and those in positions not eligible for tenure. In addition, the data is categorized by those who received their Ph.D.s <10 years from the survey (representing early career researchers and postdocs) and those 10 or more years post-Ph.D.. The change in the academic employment landscape for these recent Ph.D. graduates (Table 3) illustrates the radical shift occurring in Ph.D. employment at 4-year educational institutions.
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Table 3: Percentage change in recent (<10 years from degree) Ph.D.s employment at 4-year educational institutions in the United States from 2010 to 2017, calculated from NSF SDR data.
Growth in non-tenure track employment among science Ph.D.s
Where are these Ph.D.-trained scientists going? While some are moving into career fields outside of academia -- in fact the 2017 SED data showed private sector employment of science/engineering Ph.D.s (42%) was
nearly on par with educational institution employment (43%) -- many are working in non-tenure track positions that could include lecturers, adjunct faculty, research faculty, or postdoctoral positions. Table 3, above, shows the 2-3x growth in these non-tenure track positions in a period of just 7 years.
​Further examination of the 2017 data showed an astounding 17.1% (~1 in 5) of those with life science Ph.D.s employed at 4-year academic institutions were postdocs.
What is a postdoc and should I pursue one? 
"A postdoctoral scholar (postdoc) is an individual holding a doctoral degree who is engaged in a temporary period of mentored research and/or scholarly training for the purpose of acquiring the professional skills needed to pursue a career path of his or her choosing."
-National Postdoctoral Association 
While completing a postdoc has been a natural step toward securing a faculty career, it has also, unfortunately, become a holding place for Ph.D.s who have not been able to secure faculty employment. In addition, remaining a postdoc for too long may have serious effects on one’s lifetime earnings potential. In fact, many Ph.D.-trained individuals should probably not pursue a postdoc but a lack of information on career opportunities for Ph.D.-holders leaves many to default to the postdoc path.
My own story navigating the academic career path
I was one of those individuals on this default postdoc path. I had a great graduate school experience at UNC Chapel Hill and felt encouraged to stay in academia and pursue a postdoc with the goal of learning a new scientific technique (PET imaging of the dopamine system). My ultimate goal was to land a tenure-track faculty job.
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Completing my graduate training in the lab of a recently-hired faculty member certainly showed me that landing the faculty job is only step one on the path to the idealized tenured professor position. An equally difficult step is being productive to obtain tenure. A faculty member who obtains tenure needs to publish papers, secure grant funding, mentor effectively, perform service for one’s home department, and often teach. 

While the public sees a faculty job as pretty cushy -- and maybe after securing tenure it gets a bit more cushy (or at least secure in terms of your salary) -- the path to obtaining that tenured position is an arduous and tenuous one. There are so many places where one can fall off this pathway of postdoc -> assistant professor (on tenure-track) -> tenured faculty.

​Collaborative work from the
Future_PI Slack group which I have been involved with shows that every year, very qualified individuals who apply for assistant professorships don’t succeed. 

The average person (and most family members of graduate students) really has no idea the challenges Ph.D.s face in launching their careers. I know I was certainly not the first person whose parents inquired when I would be “done” with training and get a “real job”. They meant well but, like many people, assumed once someone has a Ph.D., aren’t they “done” and on the quick path to fortune?
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Acknowledging my faculty career doubts and discovering alternative career paths during my postdoc 
I spent 4.5 years as a postdoc at Vanderbilt University and it was a really wonderful time. I felt I grew as a person,
contributed important work to my field of neuroscience, and gained leadership experience in the Vanderbilt Postdoctoral Association. And while I went deep down the path toward obtaining a faculty position (even getting an onsite interview back in Spring 2018), in the back of my mind I had doubts about being a faculty member; that path just didn’t feel right. Having access to career/professional development programming at Vanderbilt helped me learn about other career paths for Ph.D.s.

I now work in career and professional development helping current graduate students and postdocs at North Carolina State University. 
You can read more about my personal career exploration journey and transition to postdoc affairs in my series of NIH BEST blog posts.
Career exploration is where it all begins
Part of the search for a post-Ph.D. or post-postdoc career is a search for yourself. This sounds kind of intimidating - and it is. But trust me when I tell you people like me do make it through a challenging career search, and along the way they often discover what is most important to their wellbeing and happiness. Seems like a pretty nice outcome after navigating the hard, twisty road to a career.

For a deeper dive: Explore the NSF data referenced in this article

See my previous Blog pieces on career exploration:
Start here
career exploration 101

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The end of work as we know it: How an increasingly automated world will change everything

12/16/2019

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Career & Professional Development, Opinion
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In a few short weeks we will be entering a new decade.

What will the 2020s hold? Technological advances continue to take shape at a blistering pace and will have effects on nearly all aspects of our lives. While most of these tech advances will be a clear benefit (improved healthcare, faster connectivity with 5G wireless, and greater access to online learning), others offer a potentially existential challenge to something most of us do for more than a third of our lives: work.  

Work in the Age of AI
The nature of work is changing rapidly. Automation and artificial intelligence (AI) are allowing machines and computer programs to take on an extraordinary variety of tasks.
We think of this as a blue-collar issue with robots now doing most of the assembly at automobile plants across the world and autonomous vehicles coming to take truckers jobs soon. The truth is, though, very few jobs are safe from automation as many jobs are quite routine and skills-based.

Any job requiring technical skill alone may eventually be subsumed by advances in AI. This leads to the important question of how does one prepare for this sea change? How can you make yourself un-replaceable by a machine?
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A 2017 McKinsey Global institute study concluded up to 800 million workers worldwide could lose their jobs to automation by 2030.

Workforce Transitions in a Time of Automation (McKinsey, Dec 2017)
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What Skills Will Be Valued in Future Work?
While it seems logical to assume that increases in AI would necessitate increased training in technical skills like computer programming, coding, engineering, or other scientific fields, the fact of the matter is that those technical skills themselves may be unsafe from the evolving capability of our machines.
Specifically, a report by the Brookings Institute where job descriptions were compared against AI-related-patents (see paper by Michael Webb at Stanford University for empirical details) found that white collar, data-intensive jobs in business, technology, engineering, and science are at greatest risk of being impacted by AI. The report quantified impact as having job duties that could be subsumed by coming AI advances. This doesn't mean AI would replace the job completely...in fact, AI may just supplement work in fields such as finance and scientific research. What is clear, though, is that only being good at a skill or technique that eventually can be automated is NOT a winning strategy. 


​"AI exposure will likely lower wages and lead to job replacement if human workers can no longer bring "extra value" that AI can't."
- Mark Muro, Senior Fellow & Lead Author of the Brookings report
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Transferable, Human-Centered Skills are Irreplaceable (for now)
What will be in demand for the foreseeable future are transferable skills. These types of skills aren't technical but rather refer to intra- and inter-personal skills that we use to get our work done efficiently, by ourselves or with others.
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LinkedIn found these 5 transferable skills to be most in demand in 2019 (based on job postings on the platform):
5. Time Management
4. Adaptability
3. Collaboration
2. Persuasion
1. Creativity
In addition, as more and more employees become tech-savvy, backgrounds that give employees perspective — historical, global, or otherwise — will become increasingly valuable. We will need to increasingly think about how our machines and interfaces are designed to interact with humans.

​Currently, machines cannot think like human beings. The AI we have today is so-called "narrow AI,” performing objective functions using data-trained models. The AI from science fiction movies where machines have human-like intelligence, so-called "artificial general intelligence," is far from a reality and may never be achieved. So, we will need people to serve as the interpretational bridge between AI and society and back again...to insert humanity into our machines and their decisions.
  
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Technical Training is NOT Enough:
The Role of Critical Thinking, Problem Solving, Data Synthesis, & Presentation Skills 

There has been an increased emphasis and interest in STEM (Science, Technology, Engineering, & Mathematics) education to prepare the next generation for a new age of work. Colleges, particularly technical schools and community colleges, have invested heavily in career and technical education that seeks to broaden technical skills currently in demand (coding, software engineering, etc...). Ironically, though, being trained in the liberal arts and humanities may be more useful in the age of AI. In addition, there is data suggesting a surplus of STEM majors in some fields (see also this piece from The Atlantic). 

It won't be so much our technical skills that differentiate us in the 21st Century economy. Rather, being able to think critically, synthesize information, present arguments persuasively, and work effectively with others will be increasingly valued. 
Anyone working in the sciences knows that our knowledge and tools change fast. So, it may not be surprising to consider the skills we value now in coding, data manipulation, and analysis may not be what is needed 20 or even 10 years from now. 
"It is not only what you know but how you learn that will set you apart."
- Thomas Friedman, author of The World is Flat: A Brief History of the Twenty-first Century
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Graduate Students & Postdocs Have the Skills Needed for the 21st Century Economy 
Having the skills to quickly dissect a problem, synthesize and interpret data, and clearly present insights and recommendations from your work are incredibly valuable. Luckily, if you have been pursuing a graduate degree or postdoctoral work, you have experience in all these areas. Each day you are working to troubleshoot problems, synthesize your data with what is already known, and form coherent narratives around your findings. You are uniquely poised to make sense of the flood of data that is and will be produced and stored from the countless scientific publications, device interactions, and web searches that occur each day. 
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Even the hot career field of data science is focused heavily on communicating insights from analyses. This skill may become even more critical as computers takeover the work of data preparation and analysis, leaving the humans to extract insights from the work. 
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Ph.D.-trained scientists are uniquely poised to be the data interpreters we will need in the 21st Century. 
How to Hone & Leverage Your Transferable Skills Into Meaningful Work 
A changing world demands individuals who can change with it. Flexibility and the ability the learn and adapt to new technology will be crucial. Scientists possess these and other transferable skills but need to more effectively hone and communicate them to potential employers.
​In addition, current graduate students and postdocs must avoid becoming so focused in one domain or technique that they don't develop the transferable skills needed to succeed in the 21st Century economy. 
How can current trainees practice and perfect their transferable skills? 
Develop Teamwork & Leadership Skills
Taking leadership roles or volunteering in organizations that you are passionate about (including graduate student and postdoc associations) allows you to give back to your community while also honing your teamwork and leadership skills (for example, see). You can look to get involved with local or national organizations or local chapters of national organizations, potentially in research or career areas that interest you. 
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Volunteering within an organization while continuing in your current role will also force you to improve your time and project management skills as you seek to fulfill your many obligations. In addition, working with others in these organizations, especially those from different backgrounds than yours, will teach you the importance of effective communication skills (listening, synthesizing, presenting), leadership, and consensus building to achieving success. 
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Check out Volunteer Match for community volunteering opportunities. ​
Communication Skills
You should also seek out opportunities to practice and demonstrate your communication skills. Join Toastmaters to practice your public presentation skills or volunteer to deliver a talk to a general audience (local science cafes/clubs are a great venue). You can also start posting articles on the web to demonstrate your written communication skills (LinkedIn has a great self-publication feature). Showing you can speak to a general audience and not just academics is crucial. Your future coworkers and customers will have a variety of backgrounds and speaking to them in an accessible way will increase the rapport you can build with them.  ​
Final Thoughts
While ​the future of work in the age of automation may seem scary, there is the real possibility that increased efficiencies will free us to do tasks that are mentally stimulating and personally rewarding. Instead of slaving over data we will be able to spend our time thinking about how it can be used to better the human condition. We will be able to spend more time interacting with one another instead of at our screens doing the menial tasks that often accompany knowledge-based work. 
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A more automated and efficient world will provide us more time to do what we enjoy and give back to others: to do meaningful work. By freeing us of routine, tedious tasks, AI also has the ability to unlock the vast untapped potential in so many of us...to allow us to pursue work and activities that are not motivated so much by their utility and profitability (as the machines will do much of that) as by their ability to bring happiness to our and others lives.
That is certainly a future worth aspiring towards.   
Further Reading
AI & Work

Where Machines Could Replace Humans - and where they can't (yet)

What jobs are affected by AI? Better-paid, better-educated workers face the most exposure

Is Technology About to Decimate White-Collar Work?

When Will AI Exceed Human Performance? Evidence from AI Experts

​
In the Age of AI (PBS Frontline documentary)

Human Flourishing in the AI Age - We Need a New Story


Education & the 21st Century Labor Market 
The Myth of the Science and Engineering Shortage
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STEM Crisis of STEM Surplus? Yes & Yes

A Humanities Degree is Worth Much More Than You Realize

The Growing Importance of Social Skills in the Labor Market

You Can Do Anything: The Surprising Power of a "Useless" Liberal Arts Education (book)

The Future of Work
​Meaningful Work: Viktor Frankl's Legacy for the 21st Century (book)

Life's Great Question: Discover How You Contribute to the World (book)

The Globotics Upheaval: Globalization, Robotics, & the Future of Work (book)

MIT Initiative on the Digital Economy 
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    A neuroscientist by training, I now work to improve the career readiness of graduate students and postdoctoral scholars.

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