Tracking Careers After a PhD

by Tanya Brown

One of the many questions I asked myself during my PhD training was “What kind of job will I get once I graduate?” This is quite a common question with many possible answers. With so many PhDs hitting the job market, where do all of us go?

It can be quite a challenge to figure out how to answer this question. Where do students go once they graduate? What do postdocs do once they are ready to move on? This sort of information would be useful for prospective graduate students and postdocs to know before they tackle academia. Career outcomes can reflect, at least in part, institutional training goals and values. Trainees deserve to know the environment that they are entering before devoting years to graduate school or postdoctoral training. Since this sort of tracking information is required for NIH training grants, it seems like this type of information is collected, at least by some programs, but may be challenging to sort through and organize at departmental and institutional levels. Communicating the results then presents a whole other set of challenges.  

Fortunately, Silva et al. (2019) provide a valuable resource by detailing how to collect, examine, and report graduate and postdoctoral career outcomes. The authors use their experience at the University of California, San Francisco, to demonstrate a method that can be used for this tracking, and they also estimate the time required for universities to institute the tracking. Since the authors completed both a retrospective study and annual data collection, they also share their tools and resources so that other institutions can complete similar studies.

The authors successfully completed these studies by:

  • Using cloud-based platforms that allowed access by multiple users, easy data storage and analysis
  • Asking participants to complete a short, five-item survey led to a high survey completion rate
  • Categorizing careers into broad, pre-defined categories ensured consistency with classification
  • Developing a project charter that set the scope and scale of the project with a timeline and specific milestones kept the project focused
  • Collaborating with campus stakeholders who may already be collecting this type of data made data collection more manageable and efficient. Graduate programs may also be more willing to share data if they can access the final analysis.

I followed up by browsing the UCSF website, and I found it quite impressive. The website contains demographic data and presents where postdocs go after they complete their training at UCSF. One of the most impressive parts about this is that the user can view the results by department and year. This type of project clearly takes significant time and effort but is will be more manageable for institutions who follow these guidelines.

One of the next steps is for trainees at more institutions to advocate for these data. This transparency seems like a win-win for institutions and trainees. Institutions have data to show for grants and stakeholders while trainees learn where they are likely to end up at the end of their training. Now it’s just a matter of making it happen.