Conversations About NIH Support of Graduate Training Programs


Monday, in a blog post on the Feedback Loop, colleagues at NIGMS outline the recent history of NIH’s efforts that impact graduate student training, as well as recent discussions beyond NIH on how to modernize and revitalize graduation education and training.

These conversations raise an important question, “Is NIH’s support of graduate-level training keeping pace with how we do science?”. This question has come greater into the forefront of our discussions in the context of reproducibility and rigor in NIH funded research. Are graduate student trainees getting the necessary training to perform rigorous experiments? If not, does it point to a larger need to rework graduate education in biomedical and behavioral research? And, of course, what is NIH’s role in this?

We are considering how to enhance our training programs to best meet the needs of modern science, and look forward to involving you in this discussion. I encourage you to take a look at the Feedback Loop blog post, and share your thoughts with NIH.


  1. A lot of discussion surrounds increasing postdoc stipends but what about PhD stipends? The NIH predoc stipends are below any stipend offered by any institution I know. The gap is not easily made up by PI’s since federal funds cannot be used to supplement these stipends.

  2. In my opinion, two factors compromise the rigor and the reproducibility of research conducted by graduate students and postdocs – (a) The Rush to Publish and (b) The PI’s Ignorance of Raw Data.

    The “counting” of papers by study sections is to be blamed for the Rush to Publish.

    The “globe-trotting” of PIs is to be blamed for their ignorance of Raw Data. Most PIs only see data that are organized into slides or figures, and when the PIs are never around but are demanding of data that support their big ideas for high impact papers, then, there is no room, no time, and no checkpoint for reproducibility.

    1. Amen, well said. Counting instead of reading with respect to pubs is a problem at the university level as well as the grant review level, and the pace needed to put out pubs and grant applications is a crushing burden on PIs.

    2. Well said. Ignorance of the actual data is also exacerbated by the growth of large labs. Even if the PI is around, he/she does not have the time to look carefully at all of the actual data produced by trainees when there are too many people with whom the PI needs to interact with on a regular basis.

  3. In my opinion, it is critical to emphasize on interdisciplinary/multidisciplinary approach in the training of our graduate students; many times I find a focused but very narrow approach without clear understanding of the potential impact of the findings to other systems and diseases. In addition, although the awareness is increasing albeit at a slow pace, the clinical and translational aspect of the research project must be emphasized in our graduate training program. The basic science research has a tremendous value to advance our knowledge, but, emphasis must be placed on the relevance of animal models or cell systems to human diseases.
    Accordingly, more emphasis and availability of research funds by the NIH on Clinical and Translational research projects would be required to gain maximum rate of return of the investment, not only from the training point of view, but also to develop better therapeutic and curative approaches. Similar to MSTP, I suggest the development of CTSTP (Clinical & Translational Science Training Program) with the requirement of mentoring and training graduate students in CTS.

  4. If we use a construction general contractor as an analogy to the research scientist, we may be able to better define what the education paradigm should look like.

    As a research scientist trainee, the student must be able to answer an important research question by developing a research project from inception through completion.

    Research scientists plan all phases of a research project.
    They must estimate the costs of resources and staffing; the expense involved in securing authorizations; and the cost for equipment that must be leased or purchased.
    Based on their estimates, research scientists prepare a budget.
    They must also prepare a timetable that establishes milestones for phases of the research project to ensure completion dates are met.

    Interacting with Others
    A number of research professionals are often involved in a research project.
    A research scientist will need to interact with a statistician to ensure the research project design will answer the research question and to ensure appropriate analyses of the outcome data.
    A research scientist will need to interact with a data center manager who develops and manages the research project database.
    The research scientist might also need to work with other professional research specialists such as treatment specialists, lab technicians or software engineers.
    The research scientist typically has direct contact with the funding organization to keep them advised on progress and issues that might arise.
    Research scientists often handle hiring and might be responsible for instructing research staff on the specifics of the research project.

    Ensuring Compliance
    On any research project, there are a number of laws and regulations that a research scientist must follow.
    Local laws might ban certain research project requirements such as school contact.
    Research scientists must follow applicable labor laws, including organized union contracts under which his employees work.
    The research scientist must know the safety regulations for various jobs and equipment operators and ensure that employees comply.

    Responding to Emergencies
    Research scientists must be prepared to handle any type of emergency that might arise.
    Staff or subjects might be injured or a critical piece of equipment may break.
    A delivery may fail to arrive and acts of nature might delay research project progress.
    The research scientist is responsible for seeing that all of these situations are correctly handled, whether they involve securing medical attention, locating backup equipment or expediting a delivery.
    When progress is delayed, the research scientist must seek ways to get the research project back on track while staying on budget.

    1. There is a very important component missing:

      Conveying results: The research scientist must be able to convey the motivation, experimental design, results, and interpretation to the scientific community, both orally and in the form of peer-reviewed publication(s).

    1. The question is, are there enough jobs for these graduates? For years, people were screaming for more wet lab biology PhDs, and now there clearly has been overproduction.

  5. The system for educating graduate students and producing new PhDs in biomedical sciences is badly broken and outdated. Resources are stretched to the acceptable limits at most institutions (ours for example is now said to have a $70 million annual operating deficit based on continuing its traditional approach to financing research, education and administration). This means that the leadership is completely focused on raising funds and cutting costs, with little time left over to consider the critically important and complex task of reinventing and restructuring graduate education. I think that NIH and possibly some of the largest, wealthiest research intensive institutions must lead the way on this, or educational programs will continue to deteriorate and in some cases collapse.
    The points made earlier in this thread about “counting papers” and “globe-trotting PIs” being at the heart of the problem deserve consideration. There are other issues that may be even more important, but these two deserve to be objectively discussed and dealt with. The problem seems that the system is riddled with perverse incentives. PIs are rewarded in many ways (reputation, promotion, salary, external funding) for publishing large numbers of meaningless and often inaccurate papers. PIs who actively train grad students (and postdocs) are often way too removed from the process of data generation and its initial assessment. This leads to vast amounts of junk science, some of which is packaged very nicely so that it masquerades as “cutting edge breakthroughs”. The priorities and responsibilities of PIs need to be redefined, and proper incentives need to be put in place to reward outcomes with real value.

  6. So many comments confirm the broken system!

    Students should have some freedom as to where to take their research. Students should be at the top of the field, not the trail end of where most (old) PIs are funded.

    Reviewers and NIH would have a much better way to control as to training – many US students still believe that a PhD in Biology is wet lab based when in reality, the future involves math, statistics and computational training.

    Students should not be allowed to be paid by PI NIH grants, but compete for stipends on their own credentials. If we shift funds away from R01s to fund students and towards TGs and particularly F31s and NSF graduate students, students should have the right to work on their own ideas, not just the PI ‘s.

    However, a holy cow will need to be slaughtered: Will we allow international students to be funded explicitly on NIH $$$? Tax payers already are funding plenty of international students via R01 etc., but currently, they are excluded from F31, NSF and TGs. Maybe we should make that controlled but explicit, i.e. start a special F category only for international students?

    At the national conference about future of graduate education (FOBGAPT) these and other ideas were discussed. There will be a sequel.

    1. Social and behavioral science, just like wet lab biology, have to become quantitative sciences.

      It can’t be any longer that math/number averse students go into social science doing qualitative research – we need fewer of those, and there are still plenty around.

      But we do need a lot more of high quality, quantitative social and behavioral scientists, as social and behavioral science is closer to what politicians use to make decisions.

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