Crowdfunding and Tribefunding in Science

Competition for government research grants to fund scientific research remains fierce in the United States. The budget of the National Institutes of Health (NIH), which constitute the major source of funding for US biological and medical research, has been increased only modestly during the past decade but it is not even keeping up with inflation. This problem is compounded by the fact that more scientists are applying for grants now than one or two decades ago, forcing the NIH to enforce strict cut-offs and only fund the top 10-20% of all submitted research proposals. Such competition ought to be good for the field because it could theoretically improve the quality of science. Unfortunately, it is nearly impossible to discern differences between excellent research grants. For example, if an institute of the NIH has a cut-off at the 13 percentile range, then a grant proposal judged to be in the top 10% would receive funding but a proposal in top 15% would end up not being funded. In an era where universities are also scaling back their financial support for research, an unfunded proposal could ultimately lead to the closure of a research laboratory and the dismissal of several members of a research team. Since the prospective assessment of a research proposal’s scientific merits are somewhat subjective, it is quite possible that the budget constraints are creating cemeteries of brilliant ideas and concepts, a world of scientific what-ifs that are forever lost.

Red Panda
Red Panda

How do we scientists deal with these scenarios? Some of us keep soldiering on, writing one grant after the other. Others change and broaden the direction of their research, hoping that perhaps research proposals in other areas are more likely to receive the elusive scores that will qualify for funding. Yet another approach is to submit research proposals to philanthropic foundations or non-profit organizations, but most of these organizations tend to focus on research which directly impacts human health. Receiving a foundation grant to study the fundamental mechanisms by which the internal clocks of plants coordinate external timing cues such as sunlight, food and temperature, for example, would be quite challenging. One alternate source of research funding that is now emerging is “scientific crowdfunding” in which scientists use web platforms to present their proposed research project to the public and thus attract donations from a large number of supporters. The basic underlying idea is that instead of receiving a $50,000 research grant from one foundation or government agency, researchers may receive smaller donations from 10, 50 or even a 100 supporters and thus finance their project.

The website experiment.com is a scientific crowdfunding platform which presents an intriguing array of projects in search of backers, ranging from “Death of a Tyrant: Help us Solve a Late Cretaceous Dinosaur Mystery!” to “Eating tough stuff with floppy jaws – how do freshwater rays eat crabs, insects, and mollusks?” Many of the projects include a video in which the researchers outline the basic goals and significance of their project and then also provide more detailed information on the webpage regarding how the funds will be used. There is also a “Discussion” section for each proposed project in which researchers answer questions raised by potential backers and, importantly, a “Results” in which researchers can report emerging results once their project is funded.

How can scientists get involved in scientific crowdfunding? Julien Vachelard and colleagues recently published an excellent overview of scientific crowdfunding. They analyzed the projects funded on experiment.com and found that projects which successfully achieved the funding goal tend to have 30-40 backers. The total amount of funds raised for most projects ranged from about $3,000 to $5,000. While these amounts are impressive, they are still far lower than a standard foundation or government agency grant in biomedical research. These smaller amounts could support limited materials to expand ongoing projects, but they are not sufficient to carry out standard biomedical research projects which cover salaries and stipends of the researchers. The annual stipends for postdoctoral research fellows alone run in the $40,000 – $55,000 range.

Vachelard and colleagues also provide great advice for how scientists can increase the likelihood of funding. Attention span is limited on the internet so researchers need to convey the key message of their research proposal in a clear, succinct and engaging manner. It is best to use powerful images and videos, set realistic goals (such as $3,000 to $5,000), articulate what the funds will be used for, participate in discussions to answer questions and also update backers with results as they emerge. Presenting research in a crowdfunding platform is an opportunity to educate the public and thus advance science, forcing scientists to develop better communication skills. These collateral benefits to the scientific enterprise extend beyond the actual amount of funding that is solicited.

One of the concerns that is voiced about scientific crowdfunding is that it may only work for “panda bear science“, i.e. scientific research involving popular themes such as cute and cuddly animals or studying life on other planets. However, a study of what actually gets funded in a scientific crowdfunding campaign revealed that the subject matter was not as important as how well the researchers communicated with their audience. A bigger challenge for the long-term success of scientific crowdfunding may be the limited amounts that are raised and therefore only cover the cost of small sub-projects but are neither sufficient to embark on exploring exciting new ideas and independent ideas nor offset salary and personnel costs. Donating $20 or $50 to a project is very different from donating amounts such as $1,000 because the latter requires not only the necessary financial resources but also a represents a major personal investment in the success of the research project. To initiate an exciting new biomedical research project in the $50,000 or $100,000 range, one needs several backers who are willing to donate $1,000 or more.

Perhaps one solution could be to move from a crowdfunding towards a tribefunding model. Crowds consist of a mass of anonymous people, mostly strangers in a confined space who do not engage each other. Tribes, on the other hand, are characterized by individuals who experience a sense of belonging and fellowship, they share and take responsibility for each other. The “tribes” in scientific tribefunding would consist of science supporters or enthusiasts who recognize the importance of the scientific work and also actively participate in discussions not just with the scientists but also with each other. Members of a paleontology tribe could include specialists and non-specialists who are willing to put in the required time to study the scientific background of a proposed paleontology research project, understand how it would advance the field and how even negative results (which are quite common in science) could be meaningful.

Tribefunding in higher education and science may sound like a novel concept but certain aspects of tribefunding are already common practice in the United States, albeit under different names. When wealthy alumni establish endowments for student scholarships, fellowship programs or research centers at their alma mater, it is in part because they feel a tribe-like loyalty towards the institutions that laid the cornerstones of their future success. The students and scholars who will benefit from these endowments are members of the same academic institution or tribe. The difference between the currently practiced form of philanthropic funding and the proposed tribefunding model is that tribe identity would not be defined by where one graduated from but instead by scientific interests.

Tribefunding could also impact the review process of scientific proposals. Currently, peer reviewers who assess the quality of scientific proposals for government agencies spend a substantial amount of time assessing the strengths and limitations of each proposal, and then convene either in person or via conference calls to arrive at a consensus regarding the merits of a proposal. Researchers often invest months of effort when they prepare research proposals which is why peer reviewers take their work very seriously and devote the required time to review each proposal carefully. Although the peer review system for grant proposals is often criticized because reviewers can make errors when they assess the quality of proposals, there are no established alternatives for how to assess research proposals. Most peer reviewers also realize that they are part of a “tribe”, with the common interest of selecting the best science. However, the definition of a “peer” is usually limited to other scientists, most of whom are tenured professors at academic institutions and does not really solicit input from non-academic science supporters.  In a tribefunding model, the definition of a “peer” would be expanded to professional scientists as well as science supporters for any given area of science. All members of the tribe could participate during the review and selection of the best projects  as well as throughout the funding period of the research projects that receive the support.

Merging the grassroots character and public outreach of crowdfunding with the sense of fellowship and active dialogue in a “scientific tribe” could take scientific crowdfunding to the next level. A comment section on a webpage is not sufficient to develop such a “tribe” affiliation but regular face-to-face meetings or conventional telephone/Skype conference calls involving several backers (independent of whether they can donate $50 or $5,000) may be more suitable. Developing a sense of ownership through this kind of communication would mean that every member of the science “tribe” realizes that they are a stakeholder. This sense of project ownership may not only increase donations, but could also create a grassroots synergy between laboratory and tribe, allowing for meaningful education and intellectual exchange.

Reference:

Vachelard J, Gambarra-Soares T, Augustini G, Riul P, Maracaja-Coutinho V (2016) A Guide to Scientific Crowdfunding. PLoS Biol 14(2): e1002373. doi:10.1371/journal.pbio.1002373

Note: An earlier version of this article was first published on the 3Quarksdaily blog.

 

ResearchBlogging.org

Vachelard J, Gambarra-Soares T, Augustini G, Riul P, & Maracaja-Coutinho V (2016). A Guide to Scientific Crowdfunding. PLoS Biology, 14 (2) PMID: 26886064

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Are American Professors More Responsive to Requests Made by White Male Students?

Less than one fifth of PhD students in the United States will be able to pursue tenure track academic faculty careers once they graduate from their program. Reduced federal funding for research and dwindling support from the institutions for their tenure-track faculty are some of the major reasons for why there is such an imbalance between the large numbers of PhD graduates and the limited availability of academic positions. Upon completing the program, PhD graduates have to consider non-academic job opportunities such as in the industry, government agencies and non-profit foundations but not every doctoral program is equally well-suited to prepare their graduates for such alternate careers. It is therefore essential for prospective students to carefully assess the doctoral program they want to enroll in and the primary mentor they would work with. The best approach is to proactively contact prospective mentors, meet with them and learn about the research opportunities in their group but also discuss how completing the doctoral program would prepare them for their future careers.

students-in-library

The vast majority of professors will gladly meet a prospective graduate student and discuss research opportunities as well as long-term career options, especially if the student requesting the meeting clarifies the goal of the meeting. However, there are cases when students wait in vain for a response. Is it because their email never reached the professor because it got lost in the internet ether or a spam folder? Was the professor simply too busy to respond? A research study headed by Katherine Milkman from the University of Pennsylvania suggests that the lack of response from the professor may in part be influenced by the perceived race or gender of the student.


Milkman and her colleagues conducted a field experiment in which 6,548 professors at the leading US academic institutions (covering 89 disciplines) were contacted via email to meet with a prospective graduate student. Here is the text of the email that was sent to each professor.

Subject Line: Prospective Doctoral Student (On Campus Next

Monday)

Dear Professor [surname of professor inserted here],

I am writing you because I am a prospective doctoral student with considerable interest in your research. My plan is to apply to doctoral programs this coming Fall, and I am eager to learn as much as I can about research opportunities in the meantime.

I will be on campus next Monday, and although I know it is short notice, I was wondering if you might have 10 minutes when you would be willing to meet with me to briefly talk about your work and any possible opportunities for me to get involved in your research. Any time that would be convenient for you would be fine with me, as meeting with you is my first priority during this campus visit.

 Thank you in advance for your consideration.

Sincerely,

[Student’s full name inserted here]

As a professor who frequently receives emails from people who want to work in my laboratory, I feel that the email used in the research study was extremely well-crafted. The student only wants a brief meeting to explore potential opportunities without trying to extract any specific commitment from the professor. The email clearly states the long-term goal – applying to doctoral programs. The tone is also very polite and the student expresses willingness of the prospective student to a to the professor’s schedule. Each email was also personally addressed with the name of the contacted faculty member.

Milkman’s research team then assessed whether the willingness of the professors to respond depended on the gender or ethnicity of the prospective student.  Since this was an experiment, the emails and student names were all fictional but the researchers generated names which most readers would clearly associate with a specific gender and ethnicity.

Here is a list of the names they used:

White male names:  Brad Anderson, Steven Smith

White female names:  Meredith Roberts, Claire Smith

Black male names: Lamar Washington, Terell Jones

Black female names: Keisha Thomas, Latoya Brown

Hispanic male names: Carlos Lopez, Juan Gonzalez

Hispanic female names: Gabriella Rodriguez, Juanita Martinez

Indian male names: Raj Singh, Deepak Patel

Indian female names: Sonali Desai, Indira Shah

Chinese Male names; Chang Huang, Dong Lin

Chinese female names: Mei Chen, Ling Wong

The researchers assessed whether the professors responded (either by agreeing to meet or providing a reason for why they could not meet) at all or whether they simply ignored the email and whether the rate of response depended on the ethnicity/gender of the student.

The overall response rate of the professors ranged from about 60% to 80%, depending on the research discipline as well as the perceived ethnicity and gender of the prospective student. When the emails were signed with names suggesting a white male background of the student, professors were far less likely to ignore the email when compared to those signed with female names or names indicating an ethnic minority background. Professors in the business sciences showed the strongest discrimination in their response rates. They ignored only 18% of emails when it appeared that they had been written by a white male and ignored 38% of the emails if they were signed with names indicating a female gender or ethnic minority background. Professors in the education disciplines ignored 21% of emails with white male names versus 35% with female or minority names. The discrimination gaps in the health sciences (33% vs 43%) and life sciences (32% vs 39%) were smaller but still significant, whereas there was no statistical difference in the humanities professor response rates. Doctoral programs in the fine arts were an interesting exception where emails from apparent white male students were more likely to be ignored (26%) than those of female or minority candidates (only 10%).

The discrimination primarily occurred at the initial response stage. When professors did respond, there was no difference in terms of whether they were able to make time for the student. The researchers also noted that responsiveness discrimination in any discipline was not restricted to one gender or ethnicity. In business doctoral programs, for example, professors were most likely to ignore emails with black female names and Indian male names. Significant discrimination against white female names (when compared to white males names) predicted an increase in discrimination against other ethnic minorities. Surprisingly, the researchers found that having higher representation of female and minority faculty at an institution did not necessarily improve the responsiveness towards requests from potential female or minority students.

This carefully designed study with a large sample size of over 6,500 professors reveals the prevalence of bias against women and ethnic minorities at the top US institutions. This bias may be so entrenched and subconscious that it cannot be remedied by simply increasing the percentage of female or ethnic minority professors in academia. Instead, it is important that professors understand that they may be victims of these biases even if they do not know it. Something as simple as deleting an email from a prospective student because we think that we are too busy to respond may be indicative of an insidious gender or racial bias that we need to understand and confront. Increased awareness and introspection as well targeted measures by institutions are the important first steps to ensure that students receive the guidance and mentorship they need, independent of their gender or ethnic background.

Reference:

Milkman KL, Akinola M, Chugh D. (2015). What Happens Before? A Field Experiment Exploring How Pay and Representation Differentially Shape Bias on the Pathway Into Organizations. Journal of Applied Psychology, 100(6), 1678–1712.

Note: An earlier version of this post was first published on the 3Quarksdaily Blog.

ResearchBlogging.org

Milkman KL, Akinola M, & Chugh D (2015). What happens before? A field experiment exploring how pay and representation differentially shape bias on the pathway into organizations. The Journal of applied psychology, 100 (6), 1678-712 PMID: 25867167

Murder Your Darling Hypotheses But Do Not Bury Them

“Whenever you feel an impulse to perpetrate a piece of exceptionally fine writing, obey it—whole-heartedly—and delete it before sending your manuscript to press. Murder your darlings.”

Sir Arthur Quiller-Couch (1863–1944). On the Art of Writing. 1916

 

Murder your darlings. The British writer Sir Arthur Quiller Crouch shared this piece of writerly wisdom when he gave his inaugural lecture series at Cambridge, asking writers to consider deleting words, phrases or even paragraphs that are especially dear to them. The minute writers fall in love with what they write, they are bound to lose their objectivity and may not be able to judge how their choice of words will be perceived by the reader. But writers aren’t the only ones who can fall prey to the Pygmalion syndrome. Scientists often find themselves in a similar situation when they develop “pet” or “darling” hypotheses.

Hypothesis via Shutterstock
Hypothesis via Shutterstock

How do scientists decide when it is time to murder their darling hypotheses? The simple answer is that scientists ought to give up scientific hypotheses once the experimental data is unable to support them, no matter how “darling” they are. However, the problem with scientific hypotheses is that they aren’t just generated based on subjective whims. A scientific hypothesis is usually put forward after analyzing substantial amounts of experimental data. The better a hypothesis is at explaining the existing data, the more “darling” it becomes. Therefore, scientists are reluctant to discard a hypothesis because of just one piece of experimental data that contradicts it.

In addition to experimental data, a number of additional factors can also play a major role in determining whether scientists will either discard or uphold their darling scientific hypotheses. Some scientific careers are built on specific scientific hypotheses which set apart certain scientists from competing rival groups. Research grants, which are essential to the survival of a scientific laboratory by providing salary funds for the senior researchers as well as the junior trainees and research staff, are written in a hypothesis-focused manner, outlining experiments that will lead to the acceptance or rejection of selected scientific hypotheses. Well written research grants always consider the possibility that the core hypothesis may be rejected based on the future experimental data. But if the hypothesis has to be rejected then the scientist has to explain the discrepancies between the preferred hypothesis that is now falling in disrepute and all the preliminary data that had led her to formulate the initial hypothesis. Such discrepancies could endanger the renewal of the grant funding and the future of the laboratory. Last but not least, it is very difficult to publish a scholarly paper describing a rejected scientific hypothesis without providing an in-depth mechanistic explanation for why the hypothesis was wrong and proposing alternate hypotheses.

For example, it is quite reasonable for a cell biologist to formulate the hypothesis that protein A improves the survival of neurons by activating pathway X based on prior scientific studies which have shown that protein A is an activator of pathway X in neurons and other studies which prove that pathway X improves cell survival in skin cells. If the data supports the hypothesis, publishing this result is fairly straightforward because it conforms to the general expectations. However, if the data does not support this hypothesis then the scientist has to explain why. Is it because protein A did not activate pathway X in her experiments? Is it because in pathway X functions differently in neurons than in skin cells? Is it because neurons and skin cells have a different threshold for survival? Experimental results that do not conform to the predictions have the potential to uncover exciting new scientific mechanisms but chasing down these alternate explanations requires a lot of time and resources which are becoming increasingly scarce. Therefore, it shouldn’t come as a surprise that some scientists may consciously or subconsciously ignore selected pieces of experimental data which contradict their darling hypotheses.

Let us move from these hypothetical situations to the real world of laboratories. There is surprisingly little data on how and when scientists reject hypotheses, but John Fugelsang and Kevin Dunbar at Dartmouth conducted a rather unique study “Theory and data interactions of the scientific mind: Evidence from the molecular and the cognitive laboratory” in 2004 in which they researched researchers. They sat in at scientific laboratory meetings of three renowned molecular biology laboratories at carefully recorded how scientists presented their laboratory data and how they would handle results which contradicted their predictions based on their hypotheses and models.

In their final analysis, Fugelsang and Dunbar included 417 scientific results that were presented at the meetings of which roughly half (223 out of 417) were not consistent with the predictions. Only 12% of these inconsistencies lead to change of the scientific model (and thus a revision of hypotheses). In the vast majority of the cases, the laboratories decided to follow up the studies by repeating and modifying the experimental protocols, thinking that the fault did not lie with the hypotheses but instead with the manner how the experiment was conducted. In the follow up experiments, 84 of the inconsistent findings could be replicated and this in turn resulted in a gradual modification of the underlying models and hypotheses in the majority of the cases. However, even when the inconsistent results were replicated, only 61% of the models were revised which means that 39% of the cases did not lead to any significant changes.

The study did not provide much information on the long-term fate of the hypotheses and models and we obviously cannot generalize the results of three molecular biology laboratory meetings at one university to the whole scientific enterprise. Also, Fugelsang and Dunbar’s study did not have a large enough sample size to clearly identify the reasons why some scientists were willing to revise their models and others weren’t. Was it because of varying complexity of experiments and models? Was it because of the approach of the individuals who conducted the experiments or the laboratory heads? I wish there were more studies like this because it would help us understand the scientific process better and maybe improve the quality of scientific research if we learned how different scientists handle inconsistent results.

In my own experience, I have also struggled with results which defied my scientific hypotheses. In 2002, we found that stem cells in human fat tissue could help grow new blood vessels. Yes, you could obtain fat from a liposuction performed by a plastic surgeon and inject these fat-derived stem cells into animal models of low blood flow in the legs. Within a week or two, the injected cells helped restore the blood flow to near normal levels! The simplest hypothesis was that the stem cells converted into endothelial cells, the cell type which forms the lining of blood vessels. However, after several months of experiments, I found no consistent evidence of fat-derived stem cells transforming into endothelial cells. We ended up publishing a paper which proposed an alternative explanation that the stem cells were releasing growth factors that helped grow blood vessels. But this explanation was not as satisfying as I had hoped. It did not account for the fact that the stem cells had aligned themselves alongside blood vessel structures and behaved like blood vessel cells.

Even though I “murdered” my darling hypothesis of fat –derived stem cells converting into blood vessel endothelial cells at the time, I did not “bury” the hypothesis. It kept ruminating in the back of my mind until roughly one decade later when we were again studying how stem cells were improving blood vessel growth. The difference was that this time, I had access to a live-imaging confocal laser microscope which allowed us to take images of cells labeled with red and green fluorescent dyes over long periods of time. Below, you can see a video of human bone marrow mesenchymal stem cells (labeled green) and human endothelial cells (labeled red) observed with the microscope overnight. The short movie compresses images obtained throughout the night and shows that the stem cells indeed do not convert into endothelial cells. Instead, they form a scaffold and guide the endothelial cells (red) by allowing them to move alongside the green scaffold and thus construct their network. This work was published in 2013 in the Journal of Molecular and Cellular Cardiology, roughly a decade after I had been forced to give up on the initial hypothesis. Back in 2002, I had assumed that the stem cells were turning into blood vessel endothelial cells because they aligned themselves in blood vessel like structures. I had never considered the possibility that they were scaffold for the endothelial cells.

This and other similar experiences have lead me to reformulate the “murder your darlings” commandment to “murder your darling hypotheses but do not bury them”. Instead of repeatedly trying to defend scientific hypotheses that cannot be supported by emerging experimental data, it is better to give up on them. But this does not mean that we should forget and bury those initial hypotheses. With newer technologies, resources or collaborations, we may find ways to explain inconsistent results years later that were not previously available to us. This is why I regularly peruse my cemetery of dead hypotheses on my hard drive to see if there are ways of perhaps resurrecting them, not in their original form but in a modification that I am now able to test.

 

Reference:

ResearchBlogging.org

Fugelsang, J., Stein, C., Green, A., & Dunbar, K. (2004). Theory and Data Interactions of the Scientific Mind: Evidence From the Molecular and the Cognitive Laboratory. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale, 58 (2), 86-95 DOI: 10.1037/h0085799

 

Note: An earlier version of this article first appeared on 3Quarksdaily.

Job Interviews Are Like Scientific Experiments

Most scientists are extremely meticulous when it comes to planning, performing and interpreting experiments. We spend many days reading up on the background literature to find out what aspects of the research is already established, and what research questions would be novel or meaningful. Once the nature and goals of the experiments are established, we generate an experimental plan and ensure that we have all the necessary equipment and supplies. While performing the experiments, we often run into unanticipated problems (“we just ran out of cell culture media”, “the cell number is half of what we had anticipated”, “the qPCR machine just broke down”) and have to quickly improvise to salvage as much of the experiment as possible. Once the experiments have been sufficiently replicated, scientists interpret the data and give rise to conclusions and novel hypotheses. One could presume that scientists would apply a similar degree of meticulous planning and execution in other situations at work that require organization skills, such as …..job interviews. Unfortunately, this is not necessarily true. I can speak from my own experience as an interview candidate in a variety of situations, as well as someone who has interviewed many graduate students, post-docs, research technicians and faculty candidates. When I look back at my career, I realize that I was not very well prepared for my job interviews and have had a “roll-of-the-dice attitude’, very different from my approach to my scientific experiments.

 

 

An interesting recent commentary in the journal Nature Immunology by Haseltine and Gould suggests that many scientists abandon the scientific process that they are so accustomed to when they are interviewing for jobs, and that this can be quite detrimental to a scientist’s job prospects. The article provides specific examples of how to approach a job interview in a “scientific” manner by applying principles and practices that we use for our scientific work to the interview process. This experiment-interview analogy can be quite useful as long as it is tailored according to the individual situation of a scientist applying for a job.

1. Background research

Before scientists perform experiments, they routinely use literature search engines such as PubMed or Web of Knowledge to find out what has been previously discovered and published. Job candidates should make use of these search engines to thoroughly research recent scientific publications from the laboratory or department in which they are interviewing. This gives the candidate a good overview of the topics of interest and productivity of their future employer, and it also allows the candidate to impress the interviewers with an in-depth and current knowledge of the area of research the interviewer is engaged in. Haseltine and Gould also make the excellent suggestion that candidates should not just rely on search engines of published scientific findings of a laboratory, but also make use of information available from grant funding agencies. The NIH (National Institutes of Health) grant search engine RePORTER, for example, is extremely useful for applicants seeking biomedical research positions in the academic world, because it gives detailed information about the grants of the future employer. It is always good to know how well-funded a future employer is, because one’s career prospects in biomedical research heavily depend on access to NIH funding. Furthermore, the proposal in the  RePORTER database include abstracts and aims of funded grants and will inform the candidate about ongoing and future research efforts, something which is not always easily discerned from published papers in the PubMed database. Lastly, many scientists and departments now have websites or blogs which should be carefully reviewed before the interview because they may also contain valuable information, such as the number of research groups in a department or whether the academic department is ensuring gender equality and adequate representation of minorities, especially for people in leadership positions.

2. Identify goals

Before we conduct experiments, we always clearly define the “read-outs”. Will we be measuring cell proliferation? Gene expression? Survival of experimental animals in response to an injury? Delineating the specific goals of an experiment allows us to ensure that the experiment is adequately powered (i.e. the proper sample size), uses the appropriate methods and that our expectations match the experimental design. For example, a “screening experiment” intended to identify a few potential cell survival signaling pathways will be conducted very differently than an experiment that definitively tests the impact a specific signal has on the cell survival.

Prior to a job interview, the candidate has to first perform an introspective analysis and clearly understand one’s own goals and expectations for the new job. Am I interested in this job because of the specific research area or because of the track record of the laboratory or department? Am I primarily interested in this job because it will provide me with an opportunity to acquire new scientific skills? Will this job prepare me for a career as an independent scientific investigator? Will the job ideally increase my chances of employment in the private sector such as a biotech company? We often only have vague notions about what we want for our future, and the time prior to a job interview is a good opportunity to narrow down and specify the short-term and long-term goals.

In addition to the introspective analysis that needs to be performed prior to the interview, the candidate needs to use the interview as an opportunity to identify the goals and expectations of the prospective employer and find out whether they match up with one’s own expectations identified during the introspective analysis.

3. Experimenting and Improvising

Experiments rarely work the first time, and even if they do, one still needs to repeat them multiple times under varying conditions to ensure their validity. The same is true for job interviews. Practice makes perfect, and it does not hurt to take advantage of multiple interview opportunities. It can also be useful to perform practice interviews with colleagues or friends, so that one gets into the habit of having a coherent answer to questions such as “Where do you see yourself in 5 years?” or “What do you see as your emerging scientific focus?”.

Improvisation is the key to successful experimentation. The best laid plans of mice and scientists often go awry, but one has to quickly adapt one’s experimental plan without compromising the scientific integrity of the data. Whether it involves running from lab to lab to chase down a missing chemical or changing the timeline of the experiment at the last minute, experimental scientists learn to become flexible while remaining rigorous. Similarly, job interviews require the same kind of flexibility. One may assume that everyone will stick to the pre-arranged itinerary regarding the prospective colleagues that a candidate will meet during the interview day, but it is not uncommon to have major last-minute changes to the itinerary. I have even seen cases where a candidate is asked to give an unplanned talk and therefore it is important to be prepared for such surprises.

4. Analyze and Interpret

Experiments always need to be analyzed and interpreted; experimental data without the proper context and interpretation can be quite meaningless. Similarly, analysis and interpretation is important for job interviews. Some of the analysis and interpretation can occur during the interview. Interviewers perusing the CV of an applicant may see the data (i.e. grades, the list of publications, abstracts that one has presented, awards, etc), but it can be very advantageous for an applicant to steer the interviewer towards one’s strengths. For example, if the applicant has published in three very different areas and appears “unfocused”, the applicant can preempt such a judgment by providing a narrative of why one worked in these seemingly different research areas.

Even after the interview, an applicant needs to sit down and analyze the “data” obtained from the interview experience. How did the interviewers respond to my career goals? Were they impressed or turned off by my research background? Which questions did I master and which ones were challenging? Were the people I met the colleagues that I could get along with? Is this really the best place in terms of helping me meet my scientific and career goals?

5. Conclusion

At the end of the interview, it is important to arrive at some sort of conclusion and a timeline for when a definitive decision can or will be made. Are there any questions that need to be resolved prior to arriving at a decision? In many cases it is also helpful for job candidates to follow-up on the subsequent day with a brief email, thanking the interviewer(s) for the opportunity to meet them. Including specific, unique points that came up during the interview will help ensure that the applicant makes a lasting impression and stick out from a large group of applicants. A generic “Thank you” is not as powerful as a “Thank you” coupled with, for example, expressing one’s excitement about the prospect of working on microbiome regulation of inflammation and proposing a few innovative experiments to address questions raised during the interview. Not only do such emails reinforce one’s interest, the responses of the interviewer(s) to an email can also help the applicant gauge the level of enthusiasm of the prospective employers.

These are just suggestions of how to approach a job interview in a logical and organized manner, something which every scientist ought to be accustomed to. The main take-home message is that the effort and time that goes into preparing for an interview is a worthwhile investment because it can have a major impact on the course of one’s scientific career.
ResearchBlogging.org

Haseltine, Derek, & Gould, James (2013). Job-search basics: a scientific approach to interviewing Nature Immunology, 14, 1199-1201 DOI: 10.1038/ni.2748

The PhD Route To Becoming a Science Writer

If you know that you want to become a science writer, should you even bother with obtaining a PhD in science? There is no easy answer to this question. Any answer is bound to reflect the personal biases and experiences of the person answering the question. The science writer Akshat Rathi recently made a good case for why an aspiring science writer should not pursue a PhD. I would like to offer a different perspective, which is primarily based on my work in the life sciences and may not necessarily apply to other scientific disciplines.

I think that obtaining a PhD in science a very reasonable path for an aspiring science writer, and I will list some of the “Pros” as well as the “Cons” of going the PhD route. Each aspiring science writer has to weigh the “Pros” and “Cons” carefully and reach a decision that is based on their individual circumstances and goals.

Pros: The benefits of obtaining a science PhD

 

1. Actively engaging in research gives you a first-hand experience of science

A PhD student works closely with a mentor to develop and test hypotheses, learn how to perform experiments, analyze data and reach conclusions based on the data. Scientific findings are rarely clear-cut. A significant amount of research effort is devoted to defining proper control groups, dealing with outliers and trouble-shooting experiments that have failed. Exciting findings are not always easy to replicate. A science writer who has had to actively deal with these issues may be in a better position to appreciate these intricacies and pitfalls of scientific research than someone without this first-hand experience.

 

2. PhD students are exposed to writing opportunities

All graduate students are expected to write their own PhD thesis. Many PhD programs also require that the students write academic research articles, abstracts for conferences or applications for pre-doctoral research grants. When writing these articles, PhD students usually work closely with their faculty mentors. Most articles or grant applications undergo multiple revisions until they are deemed to be ready for submission. The process of writing an initial draft and then making subsequent revisions is an excellent opportunity to improve one’s writing skills.

Most of us are not born with an innate talent for writing. To develop writing skills, the aspiring writer needs to practice and learn from critiques of one’s peers. The PhD mentor, the members of the thesis committee and other graduate students or postdoctoral fellows can provide valuable critiques during graduate school. Even though most of this feedback will likely focus on the science and not the writing, it can reveal whether or not the readers were able to clearly understand the core ideas that the student was trying to convey.

 

3. Presentation of one’s work

Most PhD programs require that students present their work at departmental seminars and at national or international conferences. Oral presentations for conferences need to be carefully crafted so that the audience learns about the background of the work, the novel findings and the implications of the research – all within the tight time constraint of a 15-20 minute time slot. A good mentor will work with PhD students to teach them how to communicate the research findings in a concise and accurate manner. Some presentations at conferences take the form of a poster, but the challenge of designing a first-rate poster is quite similar to that of a short oral presentation. One has to condense months or years of research data into a very limited space. Oral presentations as well as poster presentations are excellent opportunities to improve one’s communication skills, which are a valuable asset for any future science writer.

 

4. Peer review

Learning to perform an in-depth critical review of scientific work is an important pre-requisite for an aspiring science writer. When PhD students give presentations at departmental seminars or at conferences, they interact with a broad range of researchers, who can offer novel perspectives on the work that are distinct from what the students may have encountered in their own laboratory. Such scientific dialogue helps PhD students learn how to critically evaluate their own scientific results and realize that there can be many distinct interpretations of their data. Manuscripts or grant applications submitted by the PhD student undergo peer review by anonymous experts in the field. The reviews can be quite harsh and depressing, but they also help PhD students and their mentors identify potential flaws in their scientific work. The ability to critically evaluate scientific findings is further enhanced when PhD students participate in journal clubs to discuss published papers or when they assist their mentors in the peer review of manuscripts.

 

5. Job opportunities

Very few writers derive enough income from their writing to cover their basic needs. This is not only true for science writers, but for writers in general and it forces writers to take on jobs that help pay the bills. A PhD degree provides the aspiring science writer with a broad range of professional opportunities in academia, industry or government. After completing the PhD program, the science writer can take on such a salaried job, while building a writing portfolio and seeking out a paid position as a science writer.

 

6. Developing a scientific niche

It is not easy to be a generalist when it comes to science writing. Most successful science writers acquire in-depth knowledge in selected areas of science. This enables them to understand the technical jargon and methodologies used in that area of research and read the original scientific papers so that they do not have to rely on secondary sources for their science writing. Conducting research, writing and reviewing academic papers and attending conferences during graduate school all contribute to the development of such a scientific niche. Having such a niche is especially important when one starts out as a science writer, because it helps define the initial focus of the writing and it also provides “credentials” in the eyes of prospective employers. This does not mean that one is forever tied to this scientific niche. Science writers and scientists routinely branch out into other disciplines, once they have established themselves.

 

Cons: The disadvantages of obtaining a science PhD

 

1. Some PhD mentors abuse their graduate students

It is no secret that there are a number of PhD mentors which treat graduate students as if they were merely an additional pair of hands. Instead of being given opportunities to develop thinking and writing skills, students are sometimes forced to just produce large amounts of experimental data. 

 

2. Some of the best science writers did not obtain PhDs in science

Even though I believe that obtaining a PhD in science is a good path to becoming a science writer, I am also aware of the fact that many excellent science writers did not take this route. Instead, they focused on developing their writing skills in other venues. One such example is Steve Silberman who is a highly regarded science writer. He has written many outstanding feature articles for magazines and blog posts for his superb PLOS blog Neurotribes. Steve writes about a diverse array of topics related to neuroscience and psychology, but has also developed certain niche areas of expertise, such as autism research.

 

3. Science writer is not a career that garners much respect among academics

PhD degrees are usually obtained under the tutelage of tenure-track or tenured academics. Their natural bias is to assume that “successful” students should follow a similar career path, i.e. obtain a PhD, engage in postdoctoral research and pursue a tenure-track academic career. Unfortunately, alternate career paths, such as becoming a science writer, are not seen in a very positive light. The mentor’s narcissistic pleasure of seeing a trainee follow in one’s foot-steps is not the only reason for this. Current academic culture is characterized by a certain degree of snobbery that elevates academic research careers and looks down on alternate careers. This lack of respect for alternate careers can be very disheartening for the student. Some PhD mentors or programs may not even take on a student if he or she discloses that their ultimate goal is to become a science writer instead of pursuing a tenure-track academic career.

 

4. A day only has 24 hours

Obtaining a PhD is a full-time job. Conducting experiments, analyzing and presenting data, reading journal articles, writing chapters for the thesis and manuscripts – all of these activities are very time-consuming. It is not easy to carve out time for science writing on the side, especially if the planned science writing is not directly related to the PhD research.

 

Choosing the right environment

 

The caveats mentioned above highlight that a future science writer has to carefully choose a PhD program. The labs/mentors that publish the most papers in high-impact journals or that happen to be located in one’s favorite city may not necessarily be the ones that are best suited to prepare the student for a future career as a science writer. On the other hand, a lab that has its own research blog indicates an interest in science communication and writing. A frank discussion with a prospective mentor about the career goal of becoming a science writer will also reveal how the mentor feels about science writing and whether the mentor would be supportive of such an endeavor. The most important take home message is that the criteria one uses for choosing a PhD program have to be tailored to the career goal of becoming a science writer.

 

Image via Wikimedia Commons(Public Domain): Portrait of Dmitry Ivanovich Mendeleev wearing the Edinburgh University professor robe by Ilya Repin.