Hiring postdocs: the PI perspective

Yesterday NatureJobs published an article titled “Group dynamics: A lab of their own”. It talks about how research group size and composition relate to scientific productivity. This is an important question, which I spent a little bit of time thinking about. In particular, about two years ago I wrote this post which I provocatively titled “Is it morally acceptable to hire postdocs?” Because of this post, Chris Woolston, the author of the NatureJobs article, interviewed me and devoted whole three paragraphs of the article to my story, which can be summarized as follows.

Young and naïve postdoc Kryazhimskiy betrays his ideals and descends into unethical abyss after confronting the cruel reality of the PI world.

Well, this would be a pretty sad story, if it were actually true. Unfortunately Mr. Woolston misrepresented my position to make it fit into the archetypical story that he is trying to tell. He writes:

Sergey Kryazhimskiy, an evolutionary biologist at the University of California, San Diego, was originally dead set against hiring postdocs.

He had a plan for avoiding his ethical dilemma: he would bring in staff scientists who were committed to their lab careers.

If Mr. Woolston bothered to carefully read my entire blog post rather than just its title, he would have seen that nowhere did I say anything that could be interpreted as “I am dead set against hiring postdocs”. Nor did I have a specific plan for how I would avoid the moral (not ethical, by the way) dilemma that I posed, if I actually got a job. Instead, I listed four possible solutions for junior faculty that other people suggested to me. (1) Hire postdocs jointly with senior PIs to improve the postdocs’ chances of getting a faculty job; (2) Do not hire postdocs just as labor, hire only those who already demonstrate very good promise to become PI; (3) Do not hire postdocs at all, run lab with graduate students; (4) Hire permanent researchers instead of postdocs. Moreover, in that same post I discussed the flaws of each of these proposed solutions.

Now, fast forward to the present day. I started my lab a couple of months ago and I am trying to hire a postdoc. Why? Are there no alternatives? Am I going against my principle of fairness? Does this make me an unethical (or immoral) individual?

The main reason that I am trying to recruit a postdoc is that I want to have diversity in my lab. Diversity in all kinds of senses but particularly I want to have both junior people who will look at problems with a fresh eye and experienced people who will know how to come up with tractable research projects and execute them. I hope that a diverse lab will be productive, healthy and fun. But why not hire a staff scientist rather than a postdoc?

Here is why. Here are two additional facts that I was not aware of two years ago.

Fact #1. The difference in cost of supporting a staff scientist versus a postdoc is huge. Here are the pay scales at UCSD: postdoc, project scientist, (all). An inexperienced postdoc would have to be paid a minimum of $42,840 per year in salary, an equivalent project scientist would have to be paid $60,500. Moreover, benefits (also paid by PI on top of salary) do not exceed 35% of the salary for postdocs, but can be up to 70% of salary for permanent staff. So, a staff scientist could be as expensive as two postdocs.

Fact #2. The UPTE negotiated such contracts for staff researchers at the University of California that it much more difficult for the PI to let such lab member go, even if they do not perform very well. Moreover, they cannot be laid off due to lack of funds, while postdocs can. For example, if a PI of a senior staff researcher runs out of funds, the University will lay off a junior staff researcher from another lab and move the senior research into that now vacant position. Thus, hiring a staff scientist is a major indefinite financial commitment that affects not only you but potentially other labs.

So, a junior PI who has no history of getting a steady stream of NIH grants has to be pretty insane to start populating the lab with staff scientists. I am now convinced more than before that a shift to staff scientist-based labs is impossible without systemic changes, some of which I already outlined in another post. While there exists such a big financial gap between postdocs and staff scientists, the laws of economics will push PIs towards hiring postdocs over staff scientists. In my view, there are two key changes that need to happen in the US. (i) Abolish postdocs as a class; instead, a PhD interested in a research career would either secure a very competitive super-postdoc position or become a staff scientist. (ii) Staff scientist positions should be funded through universities (probably by a separate stream of federal money) rather than through direct grant costs, for example like it is in Switzerland.

At this point, we are still far from solving the biomedical research crisis in the middle of which we find ourselves now. Nevertheless, I feel that several important steps in the right directions have been made in the past couple of years. My former Harvard postdoc colleague Jessica Polka and her friends organized the Future of Research Symposium which at the very least generated attention to this problem. People at the top have also started to seriously discuss solutions, e.g., here. Stanford raised its minimum postdoc salary to $51,600. Finally, this summer Department of Labor will consider whether to reclassify postdocs as employees rather than trainees, which would effectively force PIs to pay postdocs a minimum salary of $50,440 – a move that I support – which will likely lead to a reduction of the postdoc pool.

So, how is my moral dilemma doing? Well, it’s still there. In hiring a postdoc, considerations for their future career are at the very top of my list. To deal with it, my plan is to implement suggestions (1) and (2) above, and then do everything in my power to help transform the research enterprise to make it more fair and sustainable.

The Academic Job Search Epic

A few months ago my (first) academic job search epic came to an end. In January 2016 I will start the Kryazhimskiy Lab at UCSD, in the Section of Ecology, Behavior and Evolution. I thought it might be useful for the next generation of applicants to summarize my experience. So, here we go.

Some stats

Let’s start with data.

2013 2014
Applications 20 29
Interviews 1 11 (+1)
Offers 0 3 (+1)

I applied for jobs two seasons in a row. I started applying in the fall of 2013 and continued throughout the fall of 2014 (I also sent out a very small number of applications in 2011, but I was clearly not ready then). My applications in the two seasons were essentially identical: same CV, same recommendation letters, same ideas in the research statement. For complete disclosure, I did rewrite my research statement in 2014 and I do think it became better. The main difference though between applications was a single line in my publication list. In June 2014 our Science paper came out. Importantly, by the time of my 2013 application, all experiments were finished and data were largely analyzed and described in my research statement. In other words, my case is a nice test of the effect of a single Science paper on academic job search performance.

The effect is striking. In 2013 I sent out 20 applications and got 1 interview. It is at that time that I wrote this depressing post. In 2014 I sent out 29 applications and got 12 interviews, one of which I declined. In fact, there were 4 departments to which I applied both in 2013 and 2014, and I got an interview at 2 of them in 2014 but none in 2013. As a result, I got 3 offers in 2014. One additional university was prepared to give an offer, but came through too late in the game. From what I hear from other colleagues who recently applied for jobs in biology, an overall 10% success rate is pretty reasonable.

What do we learn from here? I think two lessons.

First, it appears to be very important to have a major paper from your postdoc published. Not in preparation, not on bioRxiv, not in review. Published. Preferably in Cell, Science, or Nature. I guess we all know that by now.

Second, even if you have a major paper out, you should send 10+ applications to ensure a decent chance of success.

There are certainly exceptions to these “rules”. I think there are essentially two “tracks” for getting a job. On the slow track (which is what I did) you do a regular postdoc (or multiple), where you obtain a solid if not stellar publication record and get your name recognized in the field. To start on the fast track, you have to have a stellar PhD (i.e., one or more high-profile papers). To continue, you need to get a prestigious independent postdoc position, e.g., Harvard society fellowship, Miller fellowship, etc. Then you might be able to get a tenure-track job after just one or two years of this super-postdoc even without major publications.

Time investment

One important thing to consider in applying for jobs is time investment. Putting together an application takes a lot of time. I spent 2 to 3 weeks working full time on my research statement in 2013 and another 2 weeks in 2014. Plus one week on teaching statement. Plus 3-4 days crafting an effective cover letter. You may be able to do better than that if you are a fast writer, but even then conceptualizing your research program, coming up with specific projects, and going through two or three feedback/re-writing iterations still takes time. Adjusting your statement to different page restrictions is another time-sink factor. Finally, you might want to tailor your statement to different types of departments. For example, I applied to ecology and evolution departments and to systems biology departments. Even though all core ideas and proposed work of course remained the same, I did frame them in different ways.

Once I had a couple of versions of the research and teaching statements and the cover letter backbone, it took me about 1 day per application. I looked up the department and carefully re-read the job ad trying to understand what kind of person they might want. So, I tried to place appropriate accents in the cover letter and to a lesser extent in the research statement to make my application slightly more appealing to a particular department. I have no idea whether it played any role or not. According to this post, it might. If I read my application, I would probably conclude that the person took the application process seriously.

Given this considerable time investment, the major question is: is it worth it? If you have a good chance of getting a job the answer is obviously “yes”. The answer is not necessarily “no” even if think that your chances are not great. There are three reasons for that. First, you never know your chances until you try. Second, if you get even just one interview, it is a very valuable practice for the future. Third, even if you do not get any interviews, going through the process of writing the research statement is not a complete waste of time. Conceptualizing your research program takes a lot of time, and I truly believe it is helpful to start writing early. My current research statement is compelling, but the one I wrote back in 2011 is much less so. And I arrived at my current level of conceptualization through multiple iterations which were spaced out by several months and interspersed with reading and digesting new papers and talking with smart people. In short, writing your research statement is a fairly useful time investment. However, it has to be weighed against the time investment into actual research and paper production. And the equation is simple. If you have awesome papers, you will likely get by with a poor research statement (I know of such precedents). If you don’t have papers, a fantastic research statement will never get you even an interview.

A couple of notes on how I wrote my research statement

There are probably good guides for writing research statements out there, but here are my five distilled ingredients.

  1. Vision. In my mind, vision encompasses a deep scientific problem and a series of approaches to attack it. This is the glue that holds the whole statement together.
  2. Focus. I tried to structure my statement so that it feels like every proposed project fits with the vision rather than goes off in a different direction. The reader should feel that if you accomplish all these projects, the field will advance in a major way.
  3. Clarity. Keep in mind that the first reading will unlikely take more than 10–15 minutes. So, better to assume too little knowledge on part of the reader than too much.
  4. Expertise. I tried to demonstrate that I have enough expertise to accomplish each proposed project. In parts where my expertise was clearly lacking, I explicitly mentioned relevant collaborators at the particular institution.
  5. Scope. I was given the following advice. There have to be enough ideas in the proposal to fuel a lab for five-seven years. Estimate how much work each project will take. There should be more work than you can accomplish yourself, but not so much that it will require a whole institute.

On the importance of networking

Everybody says that networking is very important, but it is actually pretty hard to pinpoint how it actually plays in. Here is my data.

Departments Got interview Did not get
With direct connection 7 7
Without direct connection 5 10

I am showing here the numbers of departments to which I applied in 2014 stratified by the presence of at least one faculty member who knew me personally (“with direct connection”; NB: I have no information on whether this person was on the committee or not) versus no such faculty members (“without direct connections”). So, it looks like the chances of getting an interview at a department with a direct social connection are a bit better (50% vs 33%). Still, publishing (at least in high-profile journals) is a much better way to improve chances of success than networking.


My interviews began in November and finished in March. There are a couple of interesting things that I learned, both about myself and about the process.

First, the delivery of my talk varied a lot, and the only predictor that I could come up with is whether there were people in the audience who intimidated me on a purely subconscious level. The presence of such people sometimes caused me to fluster. I noticed that this behavior was aggravated by lack of sleep suppressed with coffee. The lesson is: Your body and mind can behave in unusual (annoying) ways under stress, lack of sleep, and various kinds of intoxication. These undesired behaviors can be controlled, but it is important to pay attention and not to aggravate them.

Second, the variation in the quality of the departments is staggering. I applied only to places where I could potentially see myself work and my family live. Even so, the departments where I interviewed varied from absolutely stellar (which is what I got used to during my PhD and postdoc years) to I-would-rather-quit-science-than-go-there kind of places. It’s good to keep in mind that before a physical visit you have no idea of what the department is like. Some places that you think are not even worthwhile applying to may turn out to be really great, and vice versa.

Third, my ability to predict after the interview whether I would get an offer was close to zero. The only exception were failed interviews, i.e., if I thought the interview went bad, it most certainly did. The converse was not true at all: interviews that I thought I nailed did not necessarily result in offers. After each interview, just for fun I wrote down my perceived probability of an offer (either 10%, 25%, 50%, 75%, or 90%). The average value of this probability for places that did indeed offer was 63% (±20%); and for places that did not offer it was 44% (±15%). So, barely better than coin tossing.

After the offer

I was lucky enough to receive the first verbal offer after my second interview in early December. You might think that this alleviated much of the stress of subsequent interviews, but it actually did not because the offer was from the place that was not number 1 in my internal preference list (which was misguided, see above). Moreover, when most of the interviews started, the soothing effect of the offer wore off. By January it seemed more like a distant dream than reality, and since it was a verbal offer I had no document to convince me otherwise.

In any case, in the first week of March I received two more verbal offers. After that the negotiation process began. There are several important things that I learned in this process. First, until you have a written letter in your hands, nothing is certain. I have heard of multiple cases when the unofficial offer was withdrawn. So, work towards obtaining a written letter from the first phone conversation.

Second, as in any negotiation process, it’s very important to know what you want. You have to have a very clear hierarchy of priorities. And I think it is best to put out all the “deal breakers” right out on the table. This way, it will be no surprise and hopefully no bad blood if you fail to come to an agreement.

Third (and this is an advice from a senior colleague), if you have multiple offers, you have one “trump card”. You can say “If you make X happen, I will come here”. It is likely that X will happen if it is at all in Chair’s power. Obviously, you can only say this to different places with which you negotiate sequentially.

Fourth, the success of your negotiations depends heavily on your Chair. It’s Chair’s job to convince the School (the entity that has the money) to satisfy your needs and to do other things that go beyond the University (e.g., contacting potential employees for your spouse). If the Chair is doing a great job, you will receive positive enthusiastic responses to your requests. The enthusiasm of responses is probably the best predictor of how the school and the department will treat you if you actually join. If you have to beg for every single thing (lab space, startup amount, equipment, job for spouse, housing, etc), chances are that you will have to swim against the current during your whole appointment, and you won’t get tenure without competing offers. At that point you will probably ask yourself: would I really want to be in such a place?

That’s almost all I wanted to say about my own experience. Good luck to all of those who are embarking on this miserable journey this year!

NB: I was asked a couple of specific questions which I did not answer above. Here are my answers

  1. Where did you find job ads?

I used alerts on Nature Jobs and Science Careers, I was subscribed to EvolDir, I occasionally looked through postings on AcademicJobsOnline and Vitae. In my experience, most job ads are posted in multiple venues, so missing a relevant ad (at least for US-based jobs) is almost impossible. I also was incessantly looking (and contributing) to the Ecology Wiki, which I highly recommend for maintaining sanity.

  1. What would you do differently?

If I knew my chances, I would not have applied in 2013. This would have saved some of my nerves and a lot of my time.

  1. How important is teaching experience?

Not at all, at least at places where I applied (R1). But you should still put some time in writing a good teaching statement.

  1. Is outreach important?

No, unless they specifically ask for it.

UPD (27 Aug 2015)

5. What did you do after the interview? Did you follow up or just wait for an offer?

All places where I got offers contacted me themselves. When I got the offers I informed the search committee chairs of places that have not decided yet and that I would seriously consider if they did offer.

6. What were the red-flags that led you to identify “I-would-rather-quit-science-than-go-there kind of places”?

The following questions might help.

1) Do you sense or know of any inter-departmental conflicts? 2) Are theres some awesome people, or does the place feel “stale”? 3) Are there any people who you could collaborate with (or at least talk to about your science) or will you be completely isolated? 4) Are faculty excited about their grad students?

How to improve sustainability of biomedical research?

As some of you may know, NIH recently posted a Request for Information (RFI) on optimizing funding policies and other strategies to improve impact and sustainability of biomedical research. They want us (anybody, really) to submit our thoughts on the subject, limited to 500 words per question. Here it the link and here is the ScienceCareers blog post about it. The deadline for submission is May 17.

I just submitted my response. And I urge all biomedical researchers in the US, especially all postdocs and newly minted assistant professors who have not yet forgotten the postdoc life to submit their thoughts to NIH. This is our chance to change the broken system! If you don’t know what to say, it’s a good time to start thinking about these issues. To get you started, below is my response, and here is another one by Vaibhav Pai and one more from Jessica Polka, both from the FOR gang.

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Arkadii Kryazhimskiy: Memories of My Father

On 24 March 2015 Russian newspaper Troitskiy Variant published my article about my father. Here is my English translation of it.

Arkadii Viktorovich Kryazhimskiy, mathematician and member of the Russian Academy of Sciences, passed away on November 3, 2014. This was my father. He was an exceptional scientist, a talented painter, a poet, and a writer. He was a true artist, a man with boundless imagination and a charge of warm optimism. As for me, he was my principal teacher, my point or reference, and my major supporter.

Now, after he is gone, it is impossible to fully reconstruct his personality or recreate his thoughts, feelings, goals. One can only hope to put together a coarse vastly incomplete portrait from disarrayed snippets of memory. Nevertheless, I will attempt to capture his image here for us and for our descendants.

Arkadii Kryazhimskiy

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Is it morally acceptable to hire postdocs?

I have trained dozens of Postdocs. One of them even got a faculty position.Since I started interviewing for faculty jobs, I had to seriously ponder on how I would run my potential future lab. One question in particular has been bothering me quite a lot. How many postdocs (if any) should I hire? This is what I would like to discuss here today. I will be deliberately provocative, but also probably quite naïve. So please, do share your thoughts and contradict me if you think I am wrong.

There are three principal dimensions to this question. The first dimension is of course the money: if you have money, you hire people; if you don’t, you can’t. Real decisions are made along the other dimensions.

The second dimension is productivity. Research labor comes primarily in two flavors: PhD students and postdocs. (I will discuss permanent researchers below; let’s focus on students and postdocs first.) Postdocs are more productive and more independent, but are also necessarily subject to less of principal investigator’s (PI) intellectual influence. Graduate students are less productive and less independent, but are subject to more influence and can be substantially cheaper. PhDs come in batches once a year and they are a pig in a poke: some may turn out to be brilliant, others not so much. Postdocs can be hired essentially at any time and are much more predictable. As a pragmatic PI, I would certainly hire more postdocs, if money were available. After all, a postdoc is the fastest, surest and the most cost-effective way to convert grant money into papers. So, is there any reason NOT to hire postdocs?

Unfortunately, there is the third dimension to this question. Is it moral to do so? The majority of postdocs (at least in my and closely related fields of biology) are people who themselves strive to become PIs after they leave their postdoctoral lab. So, when they join the lab, they implicitly or explicitly assume that the main payoff for their work will be their future faculty job. (Most postdocs certainly don’t work for their immediate compensation, which is rather small.) Here is the problem: Their assumption is wrong.

Let’s look at some data.

Number of PhDs and faculty jobs between 1982 and 2011

This is a figure from this paper published last year. There are two observations here. First, it shows that the number of annually awarded PhDs today is about 10 times higher than the number of annually opened faculty positions. In other words, the chance for freshly minted PhD to end up as a professor is about 10%. The infographic below made by a fellow Harvard postdoc Jessica Polka illustrates the same point very nicely. And here is another estimate that puts this chance at about 6%. These pieces of data should already be enough to conclude that that for a freshly minted PhD investing time into an postdoc is quite similar to “investing” money into gambling.

The second observation is that over the past 30 years the total number faculty positions stayed almost constant. This is very interesting if we think of academia as a reproducing population [1]: one generation of PIs “produces” the next generation of PIs. In population genetics people often model such reproducing population with the so-called Wright-Fisher model. One key feature of this model is that the total number of individuals in the population stays constant (for example because the available resources are limited). Every generation all individuals attempt to reproduce, but because the total population size cannot grow, each individual on average leaves only one surviving offspring. And this is almost exactly what happens in academia. The size of academia stays roughly constant, which means that the average PI will “produce” over their entire career only a single postdoc or graduate student who would become a PI him/herself.

Importantly, the distribution of offspring numbers in academia is far from being narrowly concentrated around 1. The majority of PIs do not leave any academic descendants at all, while a few especially fit PIs produce dozens (my PhD advisor Simon Levin is a spectacularly fit PI, for example). Leaving the causes for this variation aside, let’s consider a reasonably successful PI whose fitness is 5, which is well above the average and certainly something to strive for. If this PI plans to have, say, a 30-year career and to take, say, 1 PhD student and 1 postdoc per year on average, that’s 60 “attempted reproductions”. So, how likely is this PI’s next postdoc to be lucky enough to get a job? That’s about 8% chance. So, even for a postdoc who joins the lab of this quite successful PI, the a priori chances to achieve their goal of becoming a PI themselves are rather slim.

When I think about my potential future lab in this light, I can’t help but see my potential postdocs as people walking into a casino. And this would make me, the PI, very much like the owner of that casino, i.e., an institutions that in most cases collects the reward and sends the person home minus their cash. So, is this morally acceptable?

Where will a biology PhD take you?

Where will a biology PhD take you?

I have heard four types of answers to this question.

Answer #1. There is no problem. There are actually plenty of jobs out there. Good people always get jobs.

Answer #2. There is no problem. Postdocs are adults, they well know it’s a gamble and choose to do it anyway. Ultimately, it’s not my problem what happens to them after they leave my lab.

Answer #3. Yes, it’s a moral problem. But it’s a tough world where everyone has to fend for themselves. I need to make my career, so let the chips fall where they may.

Answer #4. Yes, it’s a moral problem, and I am trying to deal with it.

Although, I did not expect to hear answer number 1, it may be not so surprising in retrospect. It mostly comes from very successful PIs that (a) are superstars who have not had problems getting a job and (b) have succeeded, one way or another, in pushing their postdocs into jobs. So, from their perspective, the system works fine, and people who fail, fail for a reason. This answer also shows that this moral problem is substantially more severe for junior faculty whose ability to deliver on implicitly promised jobs for their postdocs is generally much weaker than that of senior big-name faculty.

Answers number 2 and 3 appear to be most common. Both of them amount to the same action, or rather lack of action, and support the current imbalanced state. The only difference is that the person in position 3 feels guilty whereas the person in position 2 does not. Either way, postdocs get hired and mostly fail to get faculty jobs themselves. The main problem with this position is how to look the prospective postdoc in the eye and convince them to work for you, despite your inability to land them into a job. This problem is similar to an apparent problem of how one would convince a person to go into the casino and gamble away their money? Naively, it seems that nobody should ever do this, knowing the odds. But a typical gambler does not know the odds! Likewise, most newly minted PhDs do not know their chances of getting a faculty job (info here and here, see also the infographic). And 90% of those who do know the odds honestly think that they belong to the successful 10%. So, the PI rarely even needs convincing, prospective postdocs come knocking on doors themselves. But for a PI who knows the odds, taking a naive postdoc is, in my view, immoral and amounts to little more than exploitation: the hired postdoc produces a benefit to the PI mostly for the promise of a future job that will likely not materialize.

Most people in category 4 that I met are themselves postdocs or very junior PIs just starting their own labs. So, what are the options for such people? I know of 4 possible options, maybe there are more.

1. Hire postdocs jointly with big-name senior PIs. This arrangement doesn’t really solve the main problem, but at least relieves the junior PI of the moral burden of overpromising to their prospective postdocs. With a big-name senior PI in the back, the chances for that postdoc to get a faculty job are somewhat higher.

2. Hire only brilliant postdocs who have a priori high chances to get a faculty job. This seems to be a reasonable but cruel strategy which favors people who are already on the “A train” and discriminates against people who were late to figure out what they want to do, even if they would have turned out to be brilliant given the chance. Moreover, it’s hard to recruit the A-trainers to a junior PI’s lab, especially if it is not in a top school.

3. Do not hire postdocs at all, run lab with graduate students only. This seems quite reasonable, although at the expense of productivity. One might object to this: Isn’t there the same problem with PhDs as with postdocs? In my view, the problem is not the same. I believe that entering a PhD program in natural sciences is not a commitment to an academic track, whereas entering a postdoc is, in most cases. Most jobs outside of academia do not require a postdoc experience, so a postdoc definitely narrows down one’s options. In contrast, a PhD generally widens the options. So, in my view, most PhDs should not go onto the academic track. But in general having more educated people in the non-academic world is good, especially given how many people do not believe in evolution or what idiots oversee science in Congress. A more detailed discussion of this subject is a topic for another day.

4. Hire permanent researchers instead of postdocs. This I think is closer to a fundamental resolution of the problem. Rather than hiring a short-term postdoc by dangling a future faculty job in front of them, it is far more fair to hire a researcher permanently with a salary and benefits adequate to their experience. Although the current funding system is not particularly suitable for this – obviously, permanent researchers should be paid by the university not by grants – it can be done. A permanent researcher also becomes a great asset for the lab as they accumulate valuable skills.

To conclude this long post, I would like to leave you, the reader, with some questions. If you are a graduate student, ask yourself whether you really want to enter the academic track. Unless you are an A-trainer, are you willing to gamble on 3+ years of your life? If you are a postdoc aspiring to be a PI, how would you run your lab so that it is fair to people you hire? If you are a PI, do your postdocs work for the promise of a future faculty job? If so, do you think you are being fair to them? And given an estimate of your academic fitness from past experience, how many postdocs should you hire in the future to maintain fairness?

[1] I thank my colleague Wolfram Möbius for drawing my attention to this analogy

On the illusion of clarity

The teachings of Don Juan cover

At the top of my list of favorite books are Carlos Castaneda’s “The Teachings of Don Juan: A Yaqui Way of Knowledge” and its sequels. I think they contain a tremendous amount of wisdom. This passage is among my favorites in these books. Don Juan, a Yaqui Indian shaman and one of the main characters, describes to the author, his apprentice, the four obstacles that a person encounters in a pursuit of a long-term goal (such as becoming a shaman). These four enemies are fear, clarity, power, and old age.

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The Job Search Paradox

Here we are: 2013 is out, 2014 is in. It is time to examine one’s life in the past year. For me, it is time to examine life more generally, as for any person who is on the academic job market this season. Specifically, I would like to discuss today some issues surrounding a job search that completely or partially fails. Let’s start with the paradox that gradually arises in the applicant’s head. If you are applying for jobs, at some level you certainly believe that

(1)  You are a good scientist, i.e., you know how to ask interesting research questions, obtain solid results and publish in good journals.

If your job search is failing, it means that

(2)  No one wants to hire you.

Clearly, one of these two statements has to be wrong! Continue reading

Gene patents. The story is still not resolved!

It is hard to believe that almost one year has passed since my last post. That year was very busy, so busy in fact that I did not have any inspiration to read and write anything aside from what is directly relevant to my research. Realizing how Koyaanisqatsi my life has become, I am trying re-balance it.

I just read a small news piece in the journal Science about the ongoing U.S. Supreme Court case on gene patents. Can you believe that this issue is still unresolved? If you are a reasonable person who understands what genes are, I think it is pretty obvious that they cannot be patented. It’s like trying to patent, say, “the left lung”, or “the red blood cells”, or any other part of human organism. It’s absurd. Of course, corporations are concerned with one question, and that question is no not whether something is reasonable/ethical/fair/etc or not. The question is about money. If they could make money by patenting the left lung, they certainly would. The only reason they do not do it is because the absurdity of such intention is obvious. Lungs are big. Everybody can feel them. Everybody understands what they are doing. Nobody would accept the idea that their very own lung in their very own chest would by owned by somebody else. At least I hope nobody would! Genes on the other hand are small. Nobody can see them. Very few people really understand what they are doing. So, the absurdity of the statement that somebody would own some part of you is suddenly blurred.

Just so you know, the company that currently owns the patents to BRCA genes, and by doing so has effectively monopolized the market of breast and ovarian cancer testing, is Myriad Inc. The fact that Dr. Walter Gilbert, a Nobel Prize winner in 1980 in chemistry and a Harvard professor, sits on their board of directors and endorses such absurd legal actions is very disappointing.

If you are wondering what kind of arguments can the Myriad attorneys possibly present in favor of patenting genes, here is one:  “isolated” BRCA genes are laboratory products and, unlike chromosomes, they do not occur in nature. By the same logic, “isolated” left lungs are laboratory products and, unlike entire human bodies, do not occur in nature. (Welcome to the world of legal language.)

Good day!

Shermin and I have a number of ongoing themes in our discussions. One of them is about sustainable agriculture and how many people can our planet actually support. The latter question has a caveat of course: the answer depends on which technology one would use for growing food. I would surely think that the Earth would support more people if we grew food using conventional (i.e., not sustainable) methods compared to organic. But how much more? Twice as much? Ten times as much?

A recent paper in the journal Nature called “Comparing the yields of organic and conventional agriculture” (free full version available here) by Seufert, Ramankutty and Jonathan Foley (see his TED talk, by the way) offers some insight into the answers. The paper presents the results of a meta-analysis of comparisons of yields between conventional and organic farms. The main result is that organic farms generally have a lower yield, but how much lower depends on the details. For example, vegetables give about 30% lower yield in organic farms than in conventional farms, whereas fruits give pretty much identical yields. Another interesting observation is that, if one compares farms with “best management practices” (not very well defined what this means though) in both types of farms, organic give about 13% less yield than conventional. So, not bad at all!

One interesting likely explanation for the poorer performance of organic systems is that these systems are nitrogen limited whereas conventional systems are not. This means that, when you increase the input of nitrogen into the organic system (e.g., by dumping more fertilizer), its performance goes up. Not the case for a conventional system. The reason why nitrogen is limiting in organic systems is probably because it is released slower from decaying organic matter than is necessary for plant growth.

In short, this article give some clues as to how to optimize food production and gives some hope that organic systems will in the future be able to provide a large fraction of necessary food supply.

Securing natural capital and expanding equity to rescale civilization

I’ve just read this article by Paul Ehrlich, Peter Kareiva, and Gretchen Daily, published in Nature on 7 June 2012 (link to the original article). The authors clearly operate on a very high level (i.e., not “on the ground”), and therefore the article offers less concreteness than I would have liked. Nevertheless, here is a brief “lazy-man” summary of what I found interesting.

The main premise is: We need to do something soon

It is clear that the human population size and consumption patterns are well above what Earth could support without impairment of vital life-support systems. Population projections suggest that the world will have about 9.5 billion people in 2050 and slightly over 10 billion in 2100.

The authors offer several potential solutions, but only two of them are concrete

1. Make means of contraception accessible in developing countriesOne important win–win way to reduce fertility rates is by meeting the ‘unmet need’ for contraception; that is, by supplying safe, modern means to those who do not want a child in the next two years of their lives but are not using any means of birth control. In 53 Asian, African and Latin American countries between 1995 and 2005, an estimated 7–15% of women have an unmet need for contraception. In sub-Saharan Africa, the region where unmet need is greatest, the estimate is about 25% of married women. There are roughly 75 million unintended pregnancies in the world annually and almost half of them end in abortion. Making reproduction education and family planning universally available in the developing world could avert 20 million or more births annually, avoid over 25 million abortions, reduce maternal mortality by 25–40%, and greatly reduce the population growth rate.

2. Educate women. A second win–win way to reduce fertility rates is to raise levels of education, especially of young women. If there were a crash program of education globally, there would be roughly a billion fewer people in 2050 than if there were no effort to keep educational investment commensurate with population size. Although education and subsequent empowerment of women lowers infant and childhood mortality, this effect  is more than offset demographically by the associated growing desire and ability to have fewer children.

Studies of community-based conservation reveal that the more women are involved in local governance, the more effective forest protection and compliance with regulations. This means that women need to be explicitly targeted when designing strategies for promoting conservation and reducing environmental degradation.

I liked the concluding encouragement note

Rapid change has occurred enough times in human history in relation to fundamental aspects of culture to give hope that such change can be triggered now. One need only consider the advances in women’s rights of the past century, the transformation of the racial situation in the United States such that an African American can be elected President, and the collapse of the Soviet Union, to see that cultural change does not necessarily proceed at a glacial pace. And, just as climate change is speeding the flow of glaciers, it should speed the transition of the human enterprise towards a sustainable scale—at which care for all human beings and the natural capital upon which they depend is at the top of the political agenda. The choice seems stark and clear enough: rescaling or global bust.