What exactly is a scientific sandbox or sandpit?

Our program notes say that a sandbox is an interactive session to stimulate new collaborations, ideas, and discussion. This sounds like a great idea, but I’m having a hard time understanding what exactly it means. Should it be held in a classroom with one person up front and the rest of us interacting with him? How do we get the topic in front of us so we can discuss it?


A sandbox with Stefano Turillazzi?


A student sandbox on high school teaching?

I checked over with my friends at KnowInnovation and they run something they call a Sandpit. They say it is “an intensive, interactive workshop designed to produce radically innovative research proposals.” Now that sounds exciting. Apparently it works best if we have people together with really different backgrounds. The KI people run these in 5 day periods. What can we do in an hour or two?

Here are some thoughts. First, don’t have someone up front. For a short time, have an idea or something on the board for the topic, and maybe a few references. Then let the people mingle and talk, maybe with white boards or pads of paper around the room. Interaction, discussion, productivity even if it is only on papers around the room. If it is one person up front, even with a lot of discussion, isn’t it ultimately a lecture?

I guess this is one more example of how hard it is to really innovate in sharing ideas and moving ahead. A quick measure could be that everyone should talk and the group should be small enough that is possible.

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The trouble with paradigm shifts

Vince Formica's team will not let a beetle get to a fungus unobserved and recorded.

Vince Formica’s team will not let a beetle get to a fungus unobserved and recorded.

We biologists know well the popular version of Thomas Kuhn‘s famous work, The structure of scientific revolutions, and we all want to shift paradigms in our research. This has serious negative consequences. Let me explain.

Kuhn in his famous, paradigm shifting book in 1962 argued that knowledge does not accrete in anything like a linear fashion of facts piling on facts as a child might color in an outline of a Disney figure. Instead, careful collection of data under existing theories is jolted by new ideas, new techniques, or new data to a new way of thinking. After a paradigm shift of major scale, the questions researchers ask change, the data scientists collect takes on a new focus, and understanding is more profound. The most satisfying paradigm shifts are those that reveal new and powerful simple patterns under something once thought complex and highly variable.

There have been a number of paradigm shifts in evolutionary biology in the decades since I first embraced this absorbing field. Phylogenetics, molecular evolution, and kin selection are perhaps most important to me, but this is not a piece about the paradigm shifts of the last few decades. It is about the problem with seeking out paradigm shifts. There are many.

If a new researcher thinks that only paradigm shifts are worthy, she is likely to despair. It is not so easy to come up with even small shifts in our thinking, let alone major ones. So who can even get started if that is all that is worthy?

The opposite of a paradigm shift is normal science. How boring does that sound? But if a paradigm shift is not followed by thousands of careful studies, then who knows if it is going to hold up? We need data behind ideas, so normal science is crucial and exciting. It is also full of discovery. Maybe we need a different name that sounds more exciting than normal science.

Finally, there is the ostrich problem. Some scientists, desperate to shift paradigms, think they can do it by simply ignoring what has gone before. They name well known phenomena with new names, hoping no one will notice, but of course we do. Then it is tiresome to wade through the terminology, new and old, though most new terms for old things will simply be rejected.

Each of these three points is worthy of an essay on their own. Just remember to take a corner of the world and explain it in as open a way as you can, making use of meticulous observation, attention to all relevant theory, and exploratory tools. Normal or shifty, your work will be great!


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Quick tip for picking a great graduate program: look to the postdocs!

Postdoc Suegene Noh with first year Danielle Jimenez

Postdoc Suegene Noh with first year Danielle Jimenez


Our lab group has four postdocs.

What if there is one simple way of assessing a program, something that is flexible, responds rapidly to increasing and decreasing quality, something that applies to the whole place but can also be used to understand one potential investigator over another? It is simply the number of postdocs the program has. A program with more postdocs will generally be better overall than a program with fewer postdocs. Why should this be the case?

Postdocs are special. There are fewer of them than graduate students. They have made it through a Ph.D. program and want to continue with research. During the precious postdoc years research will claim their time, their attention, and their interest. Postdocs add a lot to a research group and to a research program or department. But their importance for choosing a Ph.D. program does not only rest on what they add to the group. Postdocs are an excellent indicator of a successful research program and a stimulating research environment. Why?


Recent graduate, Philip Queller, contemplating the graduate school decision.

Postdocs are paid for differently than graduate students. They do not get teaching assistantships. They are funded at a higher level than graduate students, currently beginning at $42,000 a year according to NIH standards for summer 2014. Their funding comes from grants the postdocs get themselves and can take anywhere, or from research funding of individual professors, or occasionally by positions funded by the university. The postdocs with their own funding vote on good programs for themselves by attending. Those with professors are an indication of successful researchers able to attract outside funding. The wise prospective graduate student will use the number and kind of postdocs as one indication of an excellent program.

Of course it would be silly to use this as a sole indicator. A younger professor may be outstanding, but not yet in a position for postdocs. I would still argue you should look at the program overall and be sure some of the other labs had postdocs.

How many postdocs should you look for before choosing a program. Well, this is not an indicator that is that quantifiable. It is just one more thing to look at, so I wouldn’t say that a program where half the labs had postdocs was worse than a program where two-thirds of the labs had postdocs. There are also a lot of other factors. But this is one that should lead you away from those generic rankings. Surely you aren’t relying on something as vague as a magazine like US News and World Report to choose your graduate program, the place where you will get your Ph.D. and be launched into the professional world?

Add the number of postdocs in the program to your complex decision. Happy postdocs are a wonderful resource and indicator of a strong program!

Posted in Graduate school, Postdocs | Tagged , , , , , | 2 Comments

How to increase research creativity: work differently!

Isn’t it too bad there isn’t a simple formula for having the best ideas? Isn’t it too bad you can’t easily find the best thing to study, something easy, fun, high impact, and easily published in PNAS? It may seem like there are no secrets to brilliance or creativity, but actually, there are. Here are a few, including some from the exceptionally innovative structure of the Guarda Evolutionary Biology course, and also some tricks I learned from the great team at KnowInnovation.

1. Separate gathering possible ideas to pursue from judging them. The KnowInnovation team does this with lots of discussion and writing on post-it notes, so ideas can be sorted later.

2. Work in teams often and listen to the quietest voice. Pay attention to how often you interrupt. Assume you are wrong and try to imagine why someone else is right. Tweak each other’s ideas to arrive at something new.IMG_5631

3.Work alone, brainstorming on your own into your most tangential thoughts, then bring them to the group for honing, sorting, operationalizing.

4. Stay away from previously published work and the internet, for awhile at least. This one is tricky, because of course you should read a lot (see next point). But, as Dieter says, you don’t want to think just like someone else, canalizing your possibilities into those paths taken previously. The Guarda course strongly discouraged any internet access at all.

5. Read a lot. You should know what others have done in the areas you work. You should also read broadly, so you know much more than what might be useful today. You should think about recall too. Can you list five big ideas in evolution of communication? mimicry? social behavior? metabiomes?

6. Push yourself to do things differently, in research and in presentations. If others use Powerpoint for their talks, give an armchair talk with words only. If others have posters for their presentations, treat your paper as a blackboard. Have a game if you can to spark the audience, but make it relevant (this group did). Would you dare to give a handwritten simple poster at a national meeting? Rosie Redfield did, at the Microbial Population Biology Gordon Conference a few years ago.

7. Don’t be afraid to be unusual. This might be in your approach, in your research question, or in the kind of team you work with. I’m still puzzled that of all the amazing things one might work on, most of the student teams at Guarda last week chose microbial projects, often involving mutualisms.

8. Write all the time. Write up your research, even the boring stuff. The writing is good practice and it might lead somewhere. Write reviews, minireviews, or even opinion pieces.

9. Be a good mentor. We learn from others whether they have more or less experience than we do. Find someone in your group, your class, and your lab, and listen to them. Talk to them. Teach them and let them teach you. This is why I like to do things like participate in workshops like this one.


The wonderful cave-like bar where we talked and watch the World Cup.

10. Connect things that don’t connect and don’t throw out weird ideas too quickly. This ties back to the first point, that you should collect ideas before judging them. Find links from different fields. Keep your standards high. Wonder, for example, how much the microbiome people might learn from actual ecologists.

The Guarda course assumed that students and faculty work in certain ways and did it differently. The students brainstormed without recourse to published work. The faculty talked without powerpoints. We grouped the students and did not give them an escape plan for difficult people. We encouraged them to take a single idea and develop it into a research project. We combined frequent conversations with the students with two rounds of paper comments and formal meetings. It is a wonder we had the energy for the bar each evening and the bonfire de fin. Next I’ll be modifying this for our own students here at Wash U. IMG_3435  IMG_5601 IMG_5555 IMG_5548 DSC00318 DSC00303 IMG_3387 IMG_5451 IMG_5488 DSC00407



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How to collaborate successfully

IMG_3520 IMG_5676 IMG_5629 IMG_5399 IMG_3260 DSC09819 IMG_2982Successful collaboration is essential for a productive research career for most people. With collaborators we can tackle bigger problems. With collaborators we can see old problems in new ways, or find a path where before were only cliffs. With collaborators we can meld the joy of personal interactions with novel research. A collaboration may be like a mutualism where different people bring different talents to the project. It may be like a social group where the parties have similar talents, but together can achieve more than any could accomplish alone.

Collaboration brings responsibilities to oneself and to the others. We must trust our collaborators and be trustworthy ourselves. We must be honest with both our data and with our ability to deliver results in a timely fashion. We must be open and share any problems. If a collaborator sends us a manuscript, we should read it promptly.

Don’t pull rank with collaborators. Many collaborators will be your own students or postdocs, or advisers, current or former. Whatever your role, get back to the others quickly, or let them know where you stand.

Be on the lookout for new collaborators with whom you might do a project neither of you would even think of alone. Make a friend at a meeting? What can you do together? New ideas come as much from talking as from reading in many cases.

I hope we facilitated some new collaborations among the young graduate students of the Guarda course in evolutionary biology. Here’s the album.

At the last bonfire I could see friendships had been forged, nearly all across nationalities and universities. I could see trust blossoming. I could see excitement for research, for their budding careers. I could see cooperation, whether it was huddling in the rainy dark for warmth, or cooperatively roasting meat, cheese, or vegetables.

With the course organization we tried to encourage different kinds of cooperation. Dieter Ebert and Sebastian Bonhoeffer put the students in four houses, then put no more than two people from one house in a research group. We mixed genders in the houses, and universities in the research groups. We made sure no group had only one woman or only one man.

We then visited the groups frequently, witnessing the budding collaborations, occasionally redirecting conversations. We saw individuals that were dominant at the beginning listen more at the end, as they gained respect for other’s ideas. We saw real teamwork even among researchers forced into teams, like arranged polygynandrous marriages. Enduring collaborations from the group will be more voluntary, but it may be that the most important thing we helped these young researchers learn is how to collaborate, how to trust, how to listen if you are talkative, and how to talk if you are quiet. I await news of their next steps with curiosity.

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Big ideas from the famous Guarda, Switzerland course in evolutionary biology


Yes, we had a free day in the middle for hiking!

Why is it so hard to come up with a big idea and a way to test it? What if you could choose any idea in any system, then plan an experiment unlimited by funds or manpower? What is your best idea? What are the most important questions in evolutionary biology? What new tools or approaches might help you solve one of them? How important it is to learn to think carefully before picking up a pipette or a butterfly net, or buying a plane ticket? Could you work with an international team to get to a brilliant project?


Dieter Ebert and Sebastian Bonhoeffer looking at flowers.


Sebastian meeting with a group.


View out our window.


House 61, with groups upstairs and downstairs. Other houses were 89, 67, 70, and 33.


Relaxing in Parsepan well after midnight.


Ready to meet with us!


Guarda, Graubunden, Switzerland.


Hearing what the faculty have to hear on their proposal at the first round.


Brainstorming is hard, even with big paper!


David Queller explaining genetic relatedness in the bar.

What questions to ask is so neglected in our teaching and learning. We learn concepts and tools, facts and history. But how do we learn to cut the newest edge? Obviously you need to know the field, its history, and the promise of new techniques, but you also need to learn to be creative. This perhaps more than anything is learned by doing. Perhaps no one does it better than the brilliant course offered to early graduate students from around the world in Guarda Switzerland by Sebastian Bonhoeffer and Dieter Ebert, along with a changing cast of visiting professors.IMG_3435

Imagine brainstorming with a group of four or five other students high in a high Alpine village. The other students come from universities in nine countries with even more nationalities among them. English is the language they use. How will group dynamics work? Can you come up with a better project in a group than you could alone? I hope so, but at the very least, science is all about convincing others of the adequacy of your approach and the importance of your methods.

This course has some unique elements. Teams of four or five work all week on their project. They turn in written versions three times, Tuesday at 11, Thursday at 4, and at the end, Friday at 2. At the last time they also give a talk on their project. They get written and oral comments from the 4 faculty members on the first two written drafts. We expect their responses to these to impact and improve the final approach.

But more than these written stages are daily personal visits by the faculty where they can ask any questions, or we can interject as they discuss on their own. Imagine brainstorming with your own group of young grad students interspersed with these expert visits, resources for any question, though of course there is nothing to say the experts will agree with each other.

Oh, did I mention this is literature free work, with the internet not allowed. What can you do just thinking hard and talking, not getting canalized into other people’s ideas, as Dieter would say.

Interactions are not only formal. The students live and cook in four different houses in groups separate from their project groups. We mixed them in all possible ways, gender, nationality, background, university. The groups also invited a faculty member for dinner each night.

Besides interacting with the students, the faculty gave armchair talks, beginning with their academic history, then moving to describing some of their research without any visual aids.

Though the faculty talks were at 9pm, we somehow found the energy to go to the private bar a hotelier opened just for us on an honor system, Parsepan.

I hope the students have learned to love science, to have an appreciation for the intricacies of designing experiments that answer interesting questions. I hope they didn’t get too frustrated with their most recalcitrant team members, and that overall they have a whole international community for their next decades of research, and feel it all began in Guarda, thanks to Sebastian Bonhoeffer and Dieter Ebert, and to the visionary Steve Stearns who started the course decades ago. With this course I hope this group can convince Sebastian that their proposals are both interesting and feasible.

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Have you started your students on writing for Wikipedia yet?

The education program at Wikipedia has as its motto: “The end of throwaway assignments and the beginning of real-world impact for student editors.”

How can we embrace this powerful motto and have our students learn through contributing to Wikipedia? I put together a slide show on this topic you can get from Slideshare: here.
Here are some principles I will try hard to get across.

1. Wikipedia is not technically difficult. You do not have to teach how because there are tons of online resources.
2. Every student should do their own piece.
3. The rough drafts, with references should go straight up on Wikipedia before polishing so they can get feedback.
4. They should be turned in separately for grading because things change rapidly on Wikipedia.
5. The work should be done in pieces. We did 500 words plus 5 references, then twice 1000 words plus 10 references. One could even do just the first piece and make a difference.
6. Look at other student’s work and comment on the talk tab.
7. Revise the work and put the changes up.
8. Additional revisions responding to the community are also good, but could be informal, not point based.
9. Join a Wikipedia project for better feed back.

It may seem a little challenging at first, but the energy of students doing original writing and defending and revising what they say is worth it!

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