I have written about weighing the value of pursuing a postdoc after completing your Ph.D. in a previous blog post. And while that post focuses on my own personal experience and opinion, I wanted to use this space to emphasize more practical advice on how to network your way to postdoc opportunities and consider the training environment in the lab/group/institution to make the most of your postdoctoral experience.

I am often asked by Ph.D. students how they should search for postdoc positions and make the most of them. Recently, I gave a presentation on the topic to a graduate class at North Carolina State University. I am sharing it here for those of you debating should you do a postdoc, how to find a good postdoc environment, and how to make the most of this training period.

Module 1: Positioning Yourself for the Postdoc
This module will help you identify your needs, preferences, and values (NPVs) to reverse-engineer your postdoc search. Using videos, case studies, worksheets, and reflection questions, you will build a game plan to leave your PhD and secure your ideal postdoc.​

Module 2: Applying for and Choosing the Right Postdoc
This module will guide you through the process of finding, interviewing, and choosing a postdoc lab that is a good fit for you. You will also learn how to apply effective negotiation strategies to help you smoothly transition out of our PhD lab and into the next stage of your career journey. 

The United State's National Science Foundation (NSF) collects a wealth of data on individuals who received their doctorate degrees from US universities. Back in April, they released their most recent batch of data from their 2019 Survey of Doctorate Recipients (SDR). The SDR provides demographic, education, and career history information from all individuals with a research doctoral degree in a science, engineering, or health (SEH) field from a university in the United States. As the SDR seeks to capture the full scope of US SEH Ph.D. employment, it surveys anyone with a Ph.D. in SEH fields from a US university regardless of year of graduation: some SDR respondents received their Ph.D.s a few years ago and some 20+  years ago. This is different from the Survey of Earned Doctorates (SED) which surveys new US Ph.D. recipients and whose data I shared in an earlier blog post. Here, I will delve into some of the trends observed in the 2019 SDR data to give those with a Ph.D. in a SEH field more insights into employment possibilities after they receive their degree.  

Across all doctorate recipients surveyed in the 2019 SDR, the US states with the largest proportion of science, engineering, or health Ph.D.s employed in them included the District of Columbia (technically not a state but represented in the state-level data; ~2.5% of the population are SEH Ph.D.s), Massachusetts (0.8%), and Maryland (0.6%). The median percent of any state's population consisting of employed SEH Ph.D.s was 0.2%. While DC, Massachusetts, and Maryland remained the top states employing biological, agricultural, and environmental life science Ph.D.s, others with high proportions of bio science Ph.D. employment included Vermont, Montana, Connecticut, North Carolina, Nebraska, California, & Washington state. Note that as these are calculated as proportion of a state's 2019 population, states with relatively low population counts (Vermont, Montana, & Nebraska) have many less Ph.D. scientists employed in them than larger states. For example, according to the 2019 SDR, there are 32,900 biological, agricultural, and environmental life science Ph.D.s employed in California (with a population of 39.5 million in 2019) while Vermont has 600 (among a population of ~600,000). 

Top 10 states for employing computer science Ph.D.s: DC, Washington, Massachusetts, California, Maryland, New York, Utah, Virginia, Oregon, New Jersey

Top 10 states for employing physical science Ph.D.s: DC, Delaware, Massachusetts, Maryland, New Mexico, Colorado, Oregon, Connecticut, California, New Jersey 
And many of these states are also top employers of engineering Ph.D.s.

Given these data you may have more luck pursuing Ph.D.-level employment in certain areas of the country over others. 

Across all SEH Ph.D.s surveyed in 2019, ~3.3% of those employed worked as a postdoc. However, the percent of employment represented by postdocs varied by field of doctorate with ~6.1% of biological, agricultural, and environmental life science Ph.D.s employed as postdocs while ~1% of computer science Ph.D.s were employed as postdocs. The percentage of engineering Ph.D.s employed as postdocs was ~2%.

Given a postdoctoral position is by definition temporary, one would expect the percent of all employed SEH Ph.D.s in a postdoc would be rather low. While the general proportion of Ph.D.s employed in postdocs is relatively low, some of the trends in postdoctoral employment are concerning. 

​Unfortunately, many postdocs have been in their positions longer than the 5 year post-Ph.D. guidance outlined by The National Academies of Sciences, Engineering, and Medicine's The Postdoctoral Experience Revisited report released in 2014 (see press release). According to the 2019 SDR data, 19% of all science postdocs were >5 years from the date of their Ph.D. being awarded and this percentage was slightly higher (21.3%) for biological, agricultural, and environmental life sciences postdocs. So, as many as 1 in 5 postdocs employed in the US are 5+ years past receiving their terminal degree.

In addition, over the past 10 years a larger proportion of the US postdoctoral population is being filled by those 5+ years post-Ph.D. In the 2010 SDR data, only 13.1% of all science postdocs and 14.9% of bio, ag, and environ life science postdocs were >5 years from their Ph.D. being awarded. And while the 2019 data is off the peak of >25% of postdocs >5 years from their Ph.D. seen in 2015, the proportion of Ph.D.s employed as postdocs >5 years from their terminal degree is still ~45% higher in 2019 than 2010. 

So, while improvements have been made around limiting long postdoctoral training periods, more needs to be done to assist these individuals in transitioning into more permanent positions either within or outside academia. 

Across all science ("all science" refers to all SEH fields surveyed except engineering and health) Ph.D.s surveyed in the 2019 SDR, ~48% work for and educational institution while ~30% are employed by a for-profit company and ~8% work for either the federal or state government. The distribution of sectors employing Ph.D.s in 2019 differed markedly by the field of the individual's doctorate degree with employment by educational institutions quite high for the social sciences (~67% of employed Ph.D.s) and for-profit companies being the largest sectors employing computer & information science (~54%) and engineering Ph.D.s (~58%).

While educational institutions are the top employers of social science Ph.D.s, they employ ~47% of those with Ph.D.s in the biological, agricultural, and environmental sciences. The proportion of engineering and chemistry Ph.D.s employed by educational institutions is even less with for-profit companies employing 50%+ of Ph.D.s from these fields. 

These data suggest certain sectors of employment may be more available to particular Ph.D. fields than others. It is difficult, however, to disentangle whether engineering and chemistry Ph.D. skills, for example, are more valued by for-profit companies than those in the social sciences or whether there is a greater openness to pursuing non-academic careers in these areas. It is possible there are things to learn from specific departments and programs who place Ph.D.s into diverse career areas that could be modeled by others. Certainly, providing diverse career pathways for Ph.D.s is critical as the "traditional" path of obtaining faculty positions becomes less available in many fields. 

Among the ~108,000 respondents to the NSF SDR 2019 survey who reported being employed at educational institutions in the US, 44.5% were tenured or on the tenure track <10 years since receiving their doctorate degree. This percentage jumped to 69.1% in those 10+ years from degree award. However, there were noticeable differences by degree field in the percentage of Ph.D.s employed at educational institutions who were tenured faculty or on the tenure-track <10 years from their Ph.D. with ~25% in this category among the biological, agricultural, and environmental life sciences to 60%+ for computer and information sciences and social sciences Ph.D.s. 

One might speculate that looking at these data for those <10 years from their Ph.D. points to a potential bottleneck to obtaining faculty positions among certain fields. Also, the length of postdoctoral positions and/or use of more contingent positions (lecturer, research associate) in educational institutions could be higher in some fields than others. The SDR data can offer some insights as the proportion of postdocs who are 5+ years from obtaining their Ph.D. is higher in the life sciences fields which also had the lowest proportion of Ph.D.s employed at educational institutions in tenured or tenure-track faculty positions (plotted in green in the graph below and above, respectively). 

While certainly the life sciences have the highest percentage of Ph.D.s employed as postdocs 5+ years from their Ph.D. and the lowest percentage of those <10 years from Ph.D. in tenure-track or tenured faculty roles, there is not perfect correspondence between lengthy postdocs and percentage of early-career Ph.D.s employed as tenured or tenure-track faculty. This could be for a myriad of reasons as the SDR data is not perfect. Remember, it only surveys individuals who earned their Ph.D.s in the United States. Thus, fields where a high percentage of workers obtain their Ph.D. outside the US are going to have less respondent representation in this survey.

For instance, we know that many postdoctoral scholars in the United States are international, who either obtained their Ph.D. in the US and continued in postdoctoral training via various visa types or who received their Ph.D. outside the US before doing a postdoc in the US. The 2019 SDR shows that ~54% of US Ph.D.s employed as postdocs are US citizens and other data from NSF shows ~49% of postdocs in the US were born oversees. In some fields including computer science and engineering, NSF estimates 55-60% of Ph.D.s working in those areas in the United States are foreign-born. Thus, the various employment trends shared so far can be affected by various limitations to employment for those individuals requiring visa sponsorship by their employer, the frequency of which may differ by Ph.D. field and the proportion of international students and scholars working in that area in the United States. I discussed some of the challenges around being an international scholar in the US (including visa restrictions) in an earlier series of blog posts.    

​Regardless of how international scholar dynamics may affect these data, it is clear from the 2019 SDR data that there are vast differences in the proportion of "early career" Ph.D.s in tenure-track or tenured faculty positions based on their degree field. ​

Much has been made of the decline in faculty positions available to Ph.D.s over recent years. The SDR data allows us to partially look at this trend by asking how the percentage of Ph.D. recipients employed at 4-year educational institutions has changed over the years. Here, I decided to look at the SDR data from 2010 and compare it to 2019.

Over the past 9 years the percentage of tenured faculty who are less than 10 years from the Ph.D. in most science fields has declined by 25-30%. The decline is less steep for tenure-track faculty in the life and physical/earth sciences. Furthermore, the proportion of engineering Ph.D.s <10 years from degree employed at educational institutions in tenure-track positions has actually increased from 2010 to 2019 based on the SDR data. Even in the engineering group, though, securing tenure by 10 years post degree has become less common, presumably as the need and/or length of postdoctoral positions have increased.  

The 2021 SDR data collection is currently underway and I will be very curious to see how these data look post-COVID. Will the percentages of early career Ph.D.s able to enter the faculty ranks fall even further? Only time will tell. 

As mentioned earlier, the prevalence of Ph.D. labor in the US who are supported on temporary visas is quite high. Many international students come to the US for their graduate training and seek employment in the country after finishing their degrees. The SDR data reports out median salaries for Ph.D. holders by citizenship status, which is plotted below by doctoral degree field. 

It is clear from these data that median salaries are lower, in aggregate, for temporary visa (J1, H1-B) holders in virtually all Ph.D. fields except mathematics & statistics AND social sciences. US permanent residents' median salaries also tend to be lower but not in all fields. In fact, in computer & information sciences and mathematics & statistics permanent residents earn slightly more than US citizens. 

It is difficult to speculate too much on these data but one potential reason for lower median salaries for temporary visa holders in particular could be the result of many of these individuals working at US universities where the visiting scholar (J1) visa category is commonly used when an individual is working as a postdoctoral scholar or some other contingent, non-tenure track position (research associate). When a temporary visa holder is employed by a company, however, they require H-1B sponsorship which is subject to a "prevailing wage" which should prevent these individuals' salaries being below "market" rate, at least in theory. The largest sponsors of H-1Bs in the US are typically companies working in the computer & information sciences or data analytics where Ph.D.s in the areas of computer science, math, and statistics would be in high demand. So, the increased salaries for temporary visa holders in those fields could be driven by who is employing the doctorate recipients (technology companies paying high wages).  

Beyond who employs Ph.D.s what work they do can drastically affect their level of compensation. As seen in the graph below, Ph.D. recipients whose primary work activity is teaching have lower median salaries than those in research & development (R&D) roles or focused more on professional services, administration, management, or sales. Clearly these data are also colored by who is employing Ph.D.s as teaching roles are almost entirely within universities whereas R&D roles could be at companies, universities, government agencies, or other employers. 

Note, however, that SDR data show the percentage of Ph.D.s whose primary work activity is teaching is ~10-15% of science and engineering Ph.D. recipients (see table, below). And there has been relatively little change in the percentages of Ph.D. recipients reporting their primary work role as teaching over the past few years. The general distribution of primary work roles for science and engineering Ph.D.s from 2017 to 2019 has remained relatively stable. And, as has been discussed in a previous post, the fact that greater than a third of science and engineering Ph.D.s report their primary work role as falling in areas outside research and development or teaching emphasizes the fact that there are many positions in administration, communications, management, and more that fall outside of the main boxes of teaching and research available to Ph.D. holders. I will be interested to see whether these distributions of work roles shift post-pandemic in the 2021 SDR data. Will there be less teaching roles? More R&D, especially in the life sciences? Or will the "something else" category continue to grow as Ph.D.s pursue more diverse career pathways?

The previous two salary graphs plot median salaries for all US Ph.D. recipients who completed the 2019 SDR. So, there are individuals in those data who are 20+ years from receiving their Ph.D.s and those who graduated only a few years ago. NSF also reports data by Ph.D. field filtered by years since doctorate which shows that the median salaries 5 years or less from being the Ph.D. awarded tend to hover around the $80,000 level though it is higher in some fields (most notably computer & information sciences). Median salaries are less different across Ph.D. science and engineering fields the further from the doctorate one looks. 

This final graph nicely illustrates the value Ph.D.s provide to their employers. One could speculate that as individuals with Ph.D. skills including critical thinking, problem solving, and knowledge synthesis also gain work experience post-Ph.D. employers value them more. Fifteen years from receiving their doctorate the median salary for all science & engineering Ph.D.s is $100,000+ and many are making well over that amount. Ph.D. training provides a valuable skillset when coupled with practical experience and knowledge of how to apply those skills through working with diverse employers. Perhaps training programs can do a better job of providing some of the practical skills valued by a variety of employers during graduate school to help aid Ph.D.s' transitions to employment after their degree? 

The NSF SDR data is an essential tool to help science and engineering graduate students, postdocs, and those who support them understand how the landscape of employment continues to evolve over time. Information on employment sectors and median salary data can also be helpful as recent Ph.D. recipients plot out the next step in their careers and understand their worth. 

There are certainly glaring issues that are evident in the NSF data as well. The fact that many Ph.D. recipients <10 years from their degree employed at educational institutions are not in tenure-track faculty or tenured faculty roles speaks to the erosion of the faculty career path for many. 

Furthermore, the proliferation of postdoctoral positions and other contingent roles is a problem. And while the number of those who received their Ph.D.s from US institutions officially employed in extended postdoctoral positions (5+ years post-Ph.D.) may be diminishing, we have less data on how many of these individuals have been captured by other job titles (such as research associate) when they "age-out" of the postdoc which may similarly lack pathways to permanent, well-compensated employment.

Certainly there are many unanswered questions in understanding the evolution of the Ph.D. workforce but NSF data provides critical insights which, when collected over time, allows for us to begin to observe changes in various employment metrics.

​I encourage you to explore the data for yourself at the links below.

Marcus Lambert, Ph.D., Associate Vice President for Research Strategy and Operations at SUNY Downstate Medical Center, and his colleagues have been interested in understanding factors that affect whether biomedical postdoctoral scholars pursue career paths as faculty, particularly at research-intensive institutions. They have published two studies on the topic over the past few years:

• ​Career choices of underrepresented and female postdocs in the biomedical sciences
• Postdocs’ advice on pursuing a research career in academia: A qualitative analysis of free-text survey responses

​Below I summarize some of the insights from these studies as well as thoughts shared by Lambert when he visited NC State in Fall 2020 to discuss his work with our graduate students, postdocs, and faculty. 

The Problem
Training and mentorship often do not align with careers available for Ph.D.s and postdocs.

Academia has traditionally viewed graduate education and postdoctoral training as preparation for a faculty career. However, estimates of the number of PhDs who enter tenure-track faculty positions range from 8 percent for life science Ph.D.s within 5 years of graduation to 20 percent for biomedical postdocs. 

Thus, our training programs must reimagine the pipeline to address the needs of a changing scientific workforce, particularly as they relate to diversity.

Lack of Diversity in Faculty: A Leaky Pipeline
Perhaps one of the more striking datapoints Dr. Lambert presented during his talk is that while the percent of underrepresented minorities earning bachelors, Ph.D.s, and entering postdocs in the biological sciences has risen over the last 20 years, their representation in full professor roles has not increased since 2001. 

Data have shown that underrepresented groups including women and certain racial/ethnic groups are less interested in a faculty career at research-intensive institutions than well-represented male researchers. 

Surveying Postdocs to Understand Their Career Choices
Dr. Lambert presented data he and his colleagues collected from postdoctoral scholars regarding their motivations for academic research careers. This research group was specifically interested in understanding what factors motivate postdocs to persist in academia. In total over 1,200 postdocs from 50 universities were surveyed. 

What were the results?
Nearly 50% of respondents reported a faculty career at a research-intensive institution as their top choice.

• Interest in a faculty career wains around year 2-3 of the postdoc, representing a potentially critical time for mentorship and career support to be provided.
• Those reporting that self-worth and career mentorship were large determinants in their career choice were more likely to indicate an interest in a research-intensive faculty career.
• Conversely, those rating financial security as a key determinant of their career choice were more likely to pursue non-faculty careers.

The Importance of Outcome Expectations & Research Self-Efficacy in Determining Faculty Career Choice
Two key metrics, outcome expectations and research self-efficacy, were higher among those interested in pursuing a faculty career versus those who chose career paths outside academia. 

• Outcome expectations: expectancy (will my effort lead to high performance), instrumentality (will performance lead to desirable outcomes), & valence (do I find the outcomes desirable) lead to a motivational force to pursue an academic research career
• Research self-efficacy: belief in one's own ability to succeed at research-related tasks (publish, secure grants, mentor students, develop novel & successful research ideas)

Female postdocs rated themselves lower in research self-efficacy and had lower outcome expectations than male postdocs. Self-worth, the sense of one's own value or worth as a person, was also a strong factor in determining career choice. In fact, the strongest predictors of underrepresented minority postdocs indicating an interest in pursuing a research-intensive faculty career were positive self-worth and high research self-efficacy. Similarly, the best predictor for women indicating an intention of pursuing an academic research position was positive self-worth. 

Research self-efficacy is associated with higher rates of first author publications, particularly for female and underrepresented postdocs. Thus, programs that increase research self-efficacy could have positive impacts on supporting postdocs and their overall research productivity.

Underrepresented Postdocs Desire More Specialized Training
Underrepresented postdocs were more likely to indicate a desire for more specialized training to assist them in pursuing a faculty career including:

• A transitioning to research independence course
• A scientific teaching course
• Fellowships and grants to support investigators like them
• Training in the application of basic science principles to community-based settings

Qualitive Insights - Advice for Pursuing an Academic Research Career
These results, just released in PLOS One, focused on investigating advice postdocs would give others pursuing academic research careers.

Specifically, the authors investigated text responses to the question:
"What advice would you give someone thinking about an academic research career?”

Data from 994 postdocs were analyzed for common themes and sentiments among a diverse sample (56% US Citizens; 62% female; 13% underrepresented minorities). 

A theme that continued to emerge in the qualitative data was the role "passion" plays in pursuing an academic research career. In fact, the authors organized many of the postdocs' responses about academic research into the concept of it being a lifestyle where one's research work and life are often one in the same.

With that in mind, other common advice centered around the need for those considering an academic career to engage in self reflection to determine if an academic research lifestyle was congruent with their values, life priorities, and personal and professional needs. Are they willing to commit long hours and much effort into academic training with no guarantee they will land a faculty position that this training traditionally prepares them for?

Pros and Cons of Postdoctoral Work
Other concepts that emerged from the postdocs' responses were that while the challenges of working as a postdoc are many (low pay, demanding workload, unanticipated setbacks, & a competitive funding and research climate), the positives in a postdoc position are scientific creativity, academic freedom, the ability to travel, and building problem solving skills.   

Luck Plays a Part in "Success"
Many of the postdoc respondents mentioned that luck can play a significant role in the success of experiments, publications, funding, and job opportunities. Thus, ensuring your self-worth is not defined by "success" in your research work is essential to maintaining your mental health and wellbeing. You only have so much control of the various outcomes that are traditionally associated with academic success but you can control how central academic success is to your life.

On a side note, I routinely encourage graduate students and postdocs to get involved in things outside the lab/work as you need other outlets to feel accomplished and successful, which can help guard against allowing research or academic success to fully define you as a person. 

Need for More Postdoc Support & Resources
Several responses to the advice for prospective academic researchers prompt emphasized the importance of strong mentorship and support while conducting postdoctoral training. Many recommended those interested in pursuing an academic research career to be proactive in researching and choosing the best work environment to complete postdoctoral training. In addition, the importance of finding multiple mentors, beyond your primary faculty supervisor, building a community of support, and asking for help are critical to success in your postdoc and beyond.

Realizing there are multiple career paths available to those with Ph.D.s and postdoctoral training and being proactive in researching your post-postdoc career options can also bolster postdocs' confidence in their futures and lessen the feeling that they must "win" the faculty lottery to be considered a "success".

Take-Home Points from Dr. Lambert's Research

• Self-worth, career mentorship, and financial security were all strong predictors of intending to pursue an academic research career (or not)
• The likelihood of underrepresented postdocs persisting in academia increases most with self-worth
• Female postdocs are slightly discouraged by lifestyle when deciding whether to pursue an academic research career
• Those postdocs most comfortable with choosing an academic research career cited the following as important factors:
  • adequate support with family and childcare
    
  • financial stability
    
  • geographical flexibility
    

These findings offer ideas about how to best support postdocs wanting to pursue faculty careers. A critical component is ensuring adequate support in the form of compensation, mentoring, training, and other resources to allow postdocs to pursue these careers with great confidence in their own abilities. 

Advice to Current Postdocs
To make the most of your postdoc, Dr. Lambert recommends:

• Be strategic about your mentorship team
• Recognize that a career in academic research is a lifestyle which may or may not be suitable for you
  • Thus, reflect on you motivation to pursue a faculty career
• Prepare for multiple career paths
• Assess your readiness & preparedness at each stage
  • For two excellent resources around readiness for a faculty career, see:
    • The Academic Career Readiness Assessment (ACRA)
      • More about the ACRA's methodology, published in CBE Life Sciences Education
    • Survey-based analysis of the academic job market (paper in eLife)
• Strengthen your research & writing skills
• Network

For further reading...
Explore more posts related to the academic career search in the Academic Packways section of the NC State Graduate School's ImPACKful blog.

The United States' National Science Foundation (NSF) collects a large amount of data on individuals receiving their doctorate degrees from U.S. universities.

These data include:

• Survey of Earned Doctorates (SED)
• Survey of Doctorate Recipients (SDR)
• Science & Engineering Indicators, published by National Center for Science and Engineering Statistics

The SED focuses on recent Ph.D. graduates from a wide range of fields (lifes sciences, physical sciences, earth sciences, engineering, education, psychology, humanities) each year 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. 

I referenced some of these data a year ago in my blog post:
​Post-Ph.D. Career Plans: Consider the Possibilities 

A new batch of SED data was released in December 2020 containing data reported in 2019.
​So, while this data does not yet capture the effect of the COVID-19 pandemic on new Ph.D. graduates, we can still look at trends in employment, earnings, and more across a wide range of disciplines. New SDR data (from 2019) will be released in April 2021. So, stay tuned for a deeper dive into insights from that survey in a future post.

How US Ph.D. Employment Has Shifted from 1999 to 2019
The SED contains much historical data, allowing us to look at trends in Ph.D. production, employment, and more. The survey's Post-Graduation Commitments data is reported from 1999 to 2019 and we'll delve more into it below. 

Ph.D.s with Post-Graduation Commitments: Employment vs. Postdoctoral Training
The data plotted below reflects the breakdown of doctorate recipients with either employment or postdoctoral training commitments post-graduation.

​Keep in mind, though, that many recent Ph.D. recipients do not report definite commitments post-graduation in the SED survey. In the data from 1999 to 2019, the average percentage of all Ph.D. recipients reporting definite post-graduation commitments is ~60%. ​

For the purposes of the data plotted above, postdoctoral training and employment are separate post-graduation commitments and the percentages in these two buckets plotted in the graphs above sum to 100% within each degree field. In these data, all post-graduation commitments are categorized as either employment or postdoctoral training. 

These historical post-graduation commitments data tell us a few things:
1) Pursuing postdoctoral training is far more common in the Life Sciences and Physical (Chemistry, Physics) & Earth Sciences
2) Data collapsed across all fields show a trend toward a lower percentage of Ph.D. recipients securing employment post graduation, with particular declines in the Humanities & Arts and Psychology & Social Sciences
3) More Humanities & Arts and Psychology & Social Science Ph.D.s with post-graduation commitments are pursuing postdoctoral training, especially over the last 10 years 
4) There are trends toward greater employment pursuit and lower engagement in postdoctoral training over the last 15 years in the Life Sciences and Physical & Earth Sciences (with a hint at a "peak postdoctoral training" level in the high 60% range in the year 2004)

Again, the data plotted above reflects only those Ph.D. recipients with definite post-graduation commitments. Let's examine the trends in the percentage of Ph.D. recipients reporting definite post-graduation commitments over the same 20-year time period, below. 

Takeaways from the graph above:
1) The "shock" of the financial crisis beginning in 2008 is evident slightly in the 2009 SED data and noticeably in the 2014 data of recent Ph.D. recipients with definite post-graduation commitments
2) While post-graduation commitment percentages recovered by 2019 in most fields, the Humanities & Arts were an exception with percentage of recent Ph.D. graduates with post-graduation commitments lower in 2019 than in 1999, 2004, or 2009
3) Mathematics & Computer Science Ph.D.s consistently experience the highest percentage of definite post-graduation commitments
​
It will be interesting to see what the SED show in relation to the COVID-19 pandemic's impact on post-graduation commitments in the coming years. 

Overall, there has been a 35.5% increase in the number of total US doctorates awarded from 1999 (41,100 Ph.D.s) to 2019 (55,703 Ph.D.s). Education doctorates (Ed.D.s; Ph.D.s) awarded decreased by 29.3% from 1999 to 2019 while the decline was 4.2% for the Humanities & Arts. The growth in Ph.D.s awarded in other fields over this twenty year time period was staggering: a doubling of degrees (118.7% increase) awarded in Mathematics & Computer Sciences and near doubling (93.3% increase) for Engineering Ph.D.s awarded. While less dramatic, the growth of Ph.D.s awarded in the Life Sciences (55.8%), Physical & Earth Sciences (53.7%), and Psychology & Social Sciences (22.8%) was still quite robust from 1999 to 2019.

​Take-home point from the Ph.D.s conferred data:
There are a lot of Ph.D.s being produced each year and while some fields may be producing recipients with good job prospects (Mathematics & Computer Sciences, 70.2% with post-graduation commitments in 2019) others continue to produce very high levels of Ph.D.s with moderate job prospects based on the SED data (Life Sciences, 62.3% with post-graduation commitments in 2019). The Humanities & Arts field showed a plateauing to slight decrease in Ph.D.s awarded over the past 20 years, suggesting this field is responding to lower "demand" for Ph.D.s (52.3% with post-graduation commitments in 2019), though some may argue not rapidly enough.

The sector employment data make clear employment in academe has declined over the past 20 years across all doctorate recipients, though more so in some fields of study. Across all doctorate recipients, there has been a 15.4% decline in the proportion of individuals employed in academe from 1999 to 2019 while the proportion employed by industry or business grew by 40% over the same time period. 

​The Ph.D. degree areas with the largest decline in the proportion of recipients working in academe from 1999 (48.1%) to 2019 (27.5%) was Mathematics & Computer Sciences at 42.8%, followed by a decline of 24.2% in the Life Sciences - from 47.5% of recipients in 1999 to 36% in 2019. In fact, as the graph above shows, the 2019 SED data indicates a larger proportion of Life Sciences Ph.D. recipients employed in industry or business than academe, a first since the data have been collected. Again, a reminder that postdoctoral training is NOT INCLUDED in these data. Rather, the graphs above display the breakdown of 2019 Ph.D. recipients with employment post-graduation commitments by sector.

Interestingly, employment in academe remained relatively stable in the fields of Psychology & Social Sciences (51.9% in 1999 and 51.7% in 2019), declined more modestly in Humanities & Arts (10.4% decline from 80.7% of 1999 Ph.D. recipients to 72.3% in 2019), and actually increased for the field of Education (20.3% increase from 47.2% of 1999 Ph.D./Ed.D. recipients to 56.8% in 2019).

Regardless, the data make clear that employment trends for recent Ph.D. recipients, especially in the Science, Technology, Engineering, & Math (STEM) fields, have changed markedly over the past 20 years.

​These data bring to light a question that continues to be asked more and more in graduate education: Are we preparing Ph.D. students for a 21st Century career landscape or one of the past? Clearly, employment prospects in academe are shrinking. 

It should be noted that there are vast differences in which sectors employ Ph.D. recipients based on their field of study, as indicated in the pie charts below. 

While not plotted above the breakdown for employment sectors for 2019 Mathematics & Computer Sciences Ph.D.s was: 64% Industry/Business, 28% Academe, 5% Government, 2% Nonprofit, & ~2% Other or Unknown. 
Clearly, being employed by industry or business sectors was the most common career path for recent Ph.D.s in STEM in 2019.
Conversely, academe is by far the largest sector employing recent Ph.D.s in Humanities & Arts, Psychology & Social Sciences, & Education.  

Clearly, in 2019, the sectors employing Ph.D.s varied WIDELY based on Ph.D. field. These facts raise the question, are we adequately preparing all Ph.D.s for their next career step given the diversity of paths they pursue?

Post-Ph.D. Plans: Pursue a Postdoc or Not?
While I have discussed my personal perspectives on the value of doing a postdoc, including using it for career exploration and self reflection, this is often a crucial decision point for many recent Ph.D. recipients. There are clearly financial considerations as postdoctoral salaries or stipends are relatively low compared to many Ph.D. holders' earning potential (discussed in more detail, below). However, the freedom and autonomy one can have in a postdoctoral position may not be matched for the rest of one's career and it can provide a nice period of scholarly and self exploration before making your next career move in academe, industry, or beyond. 

Postdoctoral training has also become necessary in many fields to be competitive for faculty positions as this additional training allows time for Ph.D. holders to build a larger collection of scholarly work, begin to demonstrate research independence, and develop crucial skills in lab management and grant writing, among other tasks required of faculty at research-intensive institutions. Teaching postdocs have also become more common for recent Ph.D.s seeking to build pedagogical and classroom management skills as they pursue teaching-focused faculty positions. 

As mentioned above in the breakdown of post-graduation commitments of recent Ph.D. recipients over the past 20 years, postdoctoral training is the majority commitment path for many fields: 59% of Life Science Ph.D. recipients in 2019 with post-graduation commitments pursued postdoctoral training while that percentage was ~56% in the Physical & Earth Sciences. The postdoctoral path is less common in other Ph.D. fields, though. 

The sheer numbers of 2019 Ph.D. recipients (collapsed across fields) pursing postdoctoral training (12,091), though, still dwarfs employment numbers in any other single employment sector (8,019 employed in academe; 7,476 employed in industry; 3,929 employment in other sectors).

​For many a postdoc is the default "next step" in their academic training and while it may fulfill this role for some, we should be empowering Ph.D. students with the information and space to decide if a postdoc makes sense for them (whether it fits into a career plan). 

Median Salaries of US Doctorate Recipients in 2019
While others have published about the financial impact of pursuing postdoctoral training versus employment post-Ph.D., the 2019 SED data allow us to look at how salaries differ between those pursuing postdoctoral training or employment by field of study (and by sex, though not discussed in this post). 

The percentage of median postdoctoral salaries to other employment salaries for new doctorate recipients demonstrate that the salary discount for pursuing postdoctoral training various greatly by field. In the Life Sciences, median postdoctoral salary ($50,000) is 61% of the median of other employment salary ($82,000). The percentage is as low as 49% in Engineering and as high as 94% in Humanities and Arts.

The median salary for recently employed doctorates also varies greatly by field. $53,000 was the median salary for Humanities and Arts doctorate recipients in 2019 while it was $68,000 in Psychology, $70,000 in Education, $85,000 in Biological and Biomedical Sciences, $95,000 in Chemistry, $102,500 in Engineering, and $120,000 in Mathematics and Computer Sciences. 

While these data are aggregated over many sub-fields and employment sectors and represent the median of a wide salary range, they hopefully allow Ph.D. holders to have a sense of the salaries they can obtain post-degree.

An interesting question these data cannot answer by themselves is whether there are more Ph.D.s interested in employment in certain sectors than there are positions, which affect their ability to secure employment. It is possible (and probable) that many individuals pursue a postdoc after their Ph.D. because they cannot secure other employment upon graduation. ​

More Data to Explore
There is a wealth of data in the SED and beyond. This post has just scratched the surface. 
Next​ month I hope to touch on some of the SED data comparing temporary visa holders and US citizens and permanent residents. In addition, 2019 SDR data should be published by NSF in April, which will allow for a deeper dive into employment trends for Ph.D.-holders in the US.

​If you are interested in exploring the data that made up this post, please visit the link below.
​You can also check out all the SED data on NSF's website.  

Conclusions
While the NSF SED data prompt several questions about the doctorate workforce and career pathways that remain to be interrogated, what is clear is that post-Ph.D. career pathways for doctorates issued in the United States are changing across a wide range of disciplines. Through data such as this, those of us interested in improving graduate student and postdoc career and professional development can hopefully share post-Ph.D. employment insights with a variety of stakeholders (students, postdocs, faculty, university administrators, & lawmakers) to influence the environment at our universities.

​We must be more intentional in considering what we are training Ph.D. students and postdocs for and how their employment prospects have changed. By doing so, we can hopefully build a responsive graduate-level training ecosystem at our universities that takes into account the future economic stability and prosperity of our Ph.D. students and postdocs. 

The week of September 21-25, 2020 is National Postdoc Appreciation Week, a time for institutions and supervisors to express their appreciation for the contributions postdoctoral scholars make in a variety of areas from research to teaching and mentoring. 

As a quick refresher, a postdoctoral scholar (postdoc) is an individual with an advanced degree (Ph.D.) engaged in a period of additional training to build the skills and experiences necessary to launch themselves into an independent career of their choosing.

While traditionally a postdoc was considered the necessary "next step" in one's training progression to ultimately obtain a faculty position, postdocs move into a variety of careers after their time in postdoctoral training.

​The goal of postdoctoral offices are to support these scholars in their career and professional development. However, many postdoc offices are under-resourced to provide this much needed support to a critical component of the scientific workforce. Many are offices of 1-2 people responsible for supporting anywhere from 300 to 1,200+ postdocs. I believe one of the missing pieces allowing postdoc offices to obtain additional support is to better measure and report on the contributions postdocs make to the academic and research institutions that employ them. 

Postdoctoral scholars contribute much to the scientific enterprise and the research and teaching missions of universities.

Despite the varied and important roles they play, postdocs are often overlooked as a key constituency by administrators and leaders at research and academic institutions in the United States and globally.

I believe that measuring postdoctoral impact on the teaching/training and research/scholarship endeavors of institutions will better illuminate the key role they play in research organizations.
​I also hope this process leads to increased institutional support for the postdoc population.

​The first task is to identify metrics that would be useful to gauge the impact postdocs have on their field, lab, peers, students, and university. Some metrics could include:

1. Papers published (# of papers published, # of 1st-authored papers published)
2. Students mentored (# of students mentored, dissertation/thesis supervision of graduate/undergraduate students)
3. Teaching (# hours lectured, # courses taught, # of students taught, course evaluations)
4. Grant money (% of contribution to advisor’s research grant applications, Co-Principal Investigator (PI) roles on grants, postdoc fellowships received)
5. Contribution to lab and project management (assisting their PI supervisors in managing experiments/projects/timelines, freeing up PIs to focus on other tasks) 
6. Patents filed, intellectual property developed
7. Service performed for the university (sitting on various committees, serving in a leadership role for a campus organization like a postdoctoral association)

​Their are also structural challenges & barriers to measuring postdoc impact in these domains. 

1. Publications are often not published until 6-12 months after the first manuscript submission. Thus, a metric of publications will show postdoc impact in the past and not current impact. Conference presentations and preprint publications by postdocs may be additional metrics one could collect to gauge short-term scholarly impact. 
2. Postdoc mentoring of students is often not formalized (or even officially allowed). While a postdoc may contribute substantially to helping a graduate student in their dissertation work, the Principal Investigator (PI) of the lab (the postdoc's supervisor) is the mentor of record.
3. Regarding teaching, postdocs are often not allowed to be “instructor of record” on courses (except in the case of the small number of teaching postdocs, whose job duties include primarily teaching) and are often discouraged from teaching in place of conducting research work. However, lecturing and other teaching roles postdocs perform should be measured as this contributes to the overall educational mission of universities.
4. In the area of grants, postdocs often contribute substantially to grant applications, whether that be in the form of preliminary data they collect/analyze or assisting PIs in conceiving and/or writing of grant proposals. However, a postdoc cannot serve as a PI (and sometimes, depending on the policy of the training institution, Co-PI) on grant applications as they are not “faculty.” Thus, quantifying postdocs’ contribution to grant money received is complicated. There is no doubt, however, that they play a role (and sometimes substantial one) in many grant applications.
5. Measuring postdoc contributions to lab management is complex. It is the PI’s role to manage their labs. Thus, even if postdocs contribute substantially in assisting them in this role, some PIs may not feel that they can acknowledge this work as it could diminish their perceived role as the lab’s director.

​Many of the challenges of measuring and acknowledging postdoctoral contributions come down to the hierarchy of academia. Postdocs are “under” PIs whose own metrics of success largely mirror that of the postdoc. While this could suggest areas where there should be mutual benefit (both postdoc and supervisor/PI benefit from publications), there could also be cases where this situation introduces conflict. For example, a PI needs to secure external funding in their name to receive tenure at most research intensive academic institutions. Postdocs also need to show the ability (or potential) to secure external funding to transition into independent, tenure-track faculty positions. If postdocs cannot receive credit for their contributions to their supervisor’s grant application(s), however, one cannot truly measure their impact in this regard. This situation can also harm postdocs’ ability to secure independent faculty positions of their own, stifling their career progression.

One immediate way to address this and that I acknowledge is occurring with many PIs is to include mention of postdoc contributions to successful grant applications in letters of reference the PIs write on their behalf. In this way, a PI can make clear that the postdoc contributed substantially to a successful research grant application and will be capable of serving as PI on their own grants if they transition to an independent faculty position of their own. 

​As the measurement of graduate student and postdoc career outcomes and progression has gained attention, so too should the measurement of postdocs’ contributions in their current roles. Standardization of the metrics used to assess postdoc contributions and impact need to be undertaken to make data robust and comparable across departments and institutions. In addition, a standardized collection method would allow data to be aggregated to quantify postdoc impact at a national or international level. 

Thus, quantifying postdoc impact will allow postdoc offices to better advocate for additional resources to support this important (but often overlooked) population. ​

​While much progress has been made in improving the working conditions and support (stipends) for postdocs in the US driven by many dedicated individuals and the efforts of the NPA, a need to move toward a more structured, data-driven approach to demonstrating their impact is needed. Only by showing the impact postdocs make can the offices who support them effectively advocate for additional institutional resources to enhance the lives and training of postdocs. By doing so, we can more effectively nurture the next generation of researchers and allow them to leverage their skills, interests, and values to improving society in the variety of careers they pursue after their postdoctoral training. 

Publications on Postdoc Impact
Bringing the lab back in: Personnel composition and scientific output at the MIT Department of Biology

Contribution of postdoctoral fellows to fast-moving and competitive scientific research

Postdocs as Mentors - When it comes to everyday mentoring and training in the sciences, postdocs are the new PIs.

Useful tools to quantify publication metrics
Pubmetric - Authorship crawler that document the publishing record for trainees and their PIs via Pubmed

Publons - Track your publications, citation metrics, peer reviews, and journal editing work in a single, easy-to-maintain profile

​SciVal - From Elsevier. Allows you to visualize your research performance, benchmark relative to peers, develop strategic partnerships, identify and analyze new, emerging research trends, and create uniquely tailored reports. 

​See also
​NC State Libraries Research Impact & Metrics Landing Page 

Academic Analytics

NPA Institutional Policy Report & Database - a great model that currently focuses on postdoc offices reporting on postdoc benefits, salaries, and numbers in addition to office size and budgets ​