It’s all about choices. We make pro/con lists all the time. We consider X variables, make some assumptions, weigh options, and decide.
In a series of posts, I’m going to objectively decide a career after my PhD. I’ll have to ignore the subjective aspects for now. This is the Vulcan approach.
Odds of becoming a professor in the US after a 5 year postdoc: ~15% (data from NIH here).* Underlined items will be addressed in the future.
- The Return on investment depends on a) the average salary, b) the opportunity cost of pursuing a different career, c) the time it takes to secure a professorship, and d) satisfaction.
A) The average salary of a starting assistant professor depends on location and institution: I will use numbers from the University of California system as an example. UC faculty salaries are determined by peer review, and are “merit” based. Salaries range from 66k-150k for year 1 assistant professors. The average salary varies by location. This is something I’ll have to address later.
B) I will crunch the numbers on different career paths later.
C) If I use the numbers from the US: The average time to a doctoral degree in biomedical science is 5.5-7 years. The average post doc length is 5 years. So on average, an 11 year investment to gain a faculty position (not really, but I’ll address this later). During these years, I could be working in industry making x salary depending on my position. I’ll address this money problem below.
D) Is satisfaction measurable? Maybe there are job satisfaction numbers available for faculty vs industry vs government vs etc.? Does “prestige” matter?
- The odds are adjustable based on Career Capital (publication history, funding history, marketable skills, networking)
A) publication and funding history are a product of luck and work. MOST of the time, more work will yield more publications and funding. I will dive into this luck/work factor later.
B) marketable skills depend on projects and opportunities. Example: Most molecular biologists may understand the applications of mass spectrometry, but would not be able to perform or analyze mass spec data. I will also address this later.
C) The value of who you know is almost impossible to objectively calculate. Unless we can assign values to each person, and determine whether that connection can help you get a faculty position. I would need data showing tenure track faculty and who they knew prior to getting that position. I will have to find a way to objectively calculate this later.
Let’s first tackle the money problem. Here are some numbers:
The average academic postdoc length is 5 years until a faculty position. This means your salary for 5 years is NIH mandated and there are no rate adjustments for cost of living. IE Salaries in Bumsville, MN are the same as San Francisco, CA.
Assuming standard deductions/exemptions for single filer, these are the salaries for an academic NIH postdoc:
- Year 1: $43,692, take home: ~39,144
- Year 2: $45,444, take home: ~40,644
- Year 3: $47,268, take home: ~42,190
- Year 4: $49,152, take home: ~43,652
- Year 5: $51,120, take home: ~45,132
If we ignore state tax and assume standard deductions, after 5 years as an academic postdoc, you will have taken home $210,762.
Now, for a postdoc in industry, we can use the salaries for a biotech in California, such as Genentech (salaries here).
- Year 1: $65,000, take home: ~55,550
- Year 2: $67,000, take home: ~57,050
- Year 3: $69,000, take home: ~58,550
- Year 4: $71,000, take home: ~60,050
- Year 5: salary assumed same as year 4, none posted.
After 5 years as a postdoc at Genentech, you will have taken home $291,250. This even assumes you spend 5 years as a postdoc. It’s possible you will have become a staff scientist before then. If you become an associate scientist after 4 years, your 5th year you will make ~112k, and that number balloons to ~$340,000.
In summary, a postdoc in academia will make $80,488 less than a postdoc in industry over the course 5 years, or roughly $16,000 per year less.
So then why doesn’t everybody do an industry postdoc then try to move back into an academic position? Several possibilities:
- Who you know. In academia, you are probably more likely to meet other academics who will affect your chances of acquiring an academic faculty position. MAYBE knowing more academics increases your chances of remaining an academic. It’d be helpful to know how these correlate.
- What you know. In academia, you learn to apply for grants. In industry, that’s not so much the case. It’s possible faculty search committees favor academic postdocs because they believe that academics are better equipped to secure grant funding, or better for an academic job. I have no idea what kind of conversations happen at faculty search committees, but I’d love to get some data on this.
- Maybe industry postdocs are harder to get? Though I doubt this because postdoc salaries are basically half of permanent staff.
- It’s also possible that people in industry become accustomed to the lifestyle (by lifestyle I mean not being broke), and choose not to go back into academia.
*I am not sure how this 15% was calculated. Some postdocs may only need 3 years to acquire a tenure-track faculty position, and some require 7 years, but the average is 5 years and 15% of all postdocs become tenure-track faculty?? Or maybe after 5-years your chances are 15%, but each year after that 15% of postdocs become faculty?? Who knows. But let’s make assumptions that it will take exactly 5 years because it’s some kind of arbitrary prerequisite.
Up next: Salaries, satisfaction and prestige.
51 confirmed cases of measles. Really? Measles? John Franklin Enders first isolated measlesvirus in 1954, and immediately began work to develop a cure. In 1960, Enders began to test his measles vaccine, and a year later he announced that the vaccine was 100% effective.
Now, more than half a century later, we have a problem. There hasn’t been a failure with the vaccine, or in the scientific process. The measles vaccine is still ~100% effective. We continue to dive deeper into molecular mechanisms of disease and come up with clever cures. A paper published just two days ago demonstrates stem cell therapy as a treatment for multiple sclerosis. However, we do have a social problem that unfortunately bleeds into global health.
It’s interesting that a lot of diseases have been well characterized and would not be an issue if not for social dysfunction. Take polio for example. The polio vaccine is extremely effective. There are enough doses of polio vaccine to go around and in fact the WHO actively sends teams of vaccinators to the last three countries where polio is endemic: Pakistan, Nigeria, and Afghanistan. Despite vaccine efficacy, there are uneducated radicals opposed to vaccination, and often these groups are violently hostile. Efforts to eradicate polio have been undermined, and it’s because of social problems. In the U.S., we may not have violent extremists opposed to vaccination, but we do have major social issues.
People hear about the 0.01% chance of adverse reaction to a vaccine, in contrast to the low odds of contracting measles in the U.S., and choose not to vaccinate their children. As far as I’m aware, there is no scientific fix for ignorance. The only real solution is education.
2. Ignorance often trumps scientific evidence.
Let’s start with Andrew Wakefield. In the late 90’s, this guy published a fraudulent paper that drew a link between vaccines, autism, and gastrointestinal disease. The paper was disproven, and after an investigation, many signs of misconduct came to light. Sure, fraud happens, and it would have been okay if not for what happened next.
Normally the conclusions of a disproven paper are disregarded. But the torch had already been lit and the anti-vaccine movement had begun. Jenny McCarthy used her public position to advocate the anti-vaccine movement, claiming her child developed autism due to vaccines. People empathize with anecdotes. (Please allow this brief interruption for an introduction to the Jenny McCarthy Body Count: Deaths attributable to the anti-vaccine movement) The torch is now a wildfire. Again, we have an example of social dysfunction that could be effectively fixed with education.
Sometimes it takes a disaster to develop a fix. Unfortunately, this problem can’t be solved with any technology or scientific advancement. Alas, social science may be relevant, thanks to measles.
A leading cause of respiratory disease in children is Respiratory Syncytial Virus (RSV), producing over 3 million cases of lower respiratory illness and about 100,000 deaths annually (Nair et al. 2010). RSV is classified as a virus in the family Paramyxoviridae, which are all non-segmented negative sense RNA viruses. Other viruses that utilize this method of replication include Mumps virus, Human Metapneumovirus (hMPV), and Henipavirus, the inspiration of the movie Contagion. Like most viruses that cause respiratory symptoms, including viruses that cause common cold, numbers of RSV infections increase in winter months when people spend more time indoors (Florida is weird).
Nearly all children will encounter RSV, but only 2-3% will require hospitalization. However, the real trouble is re-infection. Typically after your immune system develops antibodies against an antigen, it can recall the “memory” of the infection to produce specific antibodies and lymphocytes to prevent re-infection by the same agent. However, this “memory” can fade, and is of particular concern with RSV.
Challenge experiments have shown that 73% of adults became reinfected a second time within 26 months, and 43% became reinfected a third time with apparent symptoms in the majority of the cases (Hall et al. 1991). In short, the virus is capable of reinfecting healthy individuals, and immunity is relatively short-lived. This also makes it particularly difficult to produce a vaccine that does not need to be administered annually.
An appropriate adaptive immune response requires the activity of dendritic cells (DCs). In short, DCs are antigen presenter cells, and direct the T-cell and B-cell response at a particular target. DCs move from a site of infection to the lymph nodes in order to activate the proliferation of the proper lymphocytes to defend against a particular pathogen (a short video is provided below). DC migration is directed primarily by chemokines, or signalling proteins that the DC recognizes through the receptor CCR7. Without CCR7, the DC’s ability to detect chemokines is severely diminished, and without migration to the lymph node, downstream activation of the adaptive immune response is absent.
In the 2011 paper in PLOS Pathogens by Nouen et al., the authors demonstrate that RSV infection leads to a decrease in the expression of CCR7 in DCs during infection. RSV alters dendritic cell migration, and reduces DC migration to the lymph nodes.I This finding suggests that RSV is capable of regulating the immune response by reducing the activation of lymphocytes. Measles virus, another paramyxovirus, has also been shown inhibit DC migration through the modulation of CCR7 expression.
I would again like to highlight the incredible adaptability of pathogens to persist in an environment. Viruses have evolved to persist in even the harshest of all environments, including the human immune system, which is tasked with the very specific job of fighting these viruses.
Despite being known as a clinically significant human pathogen since the 1950s, a vaccine for RSV is still unavailable. However, a better understanding of how RSV modulates immunity gives us a clearer picture of why RSV vaccine development is so difficult. In contrast to Ebolavirus, RSV is very well adapted to humans, and rarely kills its host, but the disease burden of RSV is certainly significant.
Fortunately, basic research into mechanisms of pathogenesis is leading us in the right direction. But what you may believe to be a “common cold” (which may actually be caused by any number of viruses including rhinovirus, adenovirus, or coronavirus) can be RSV. Persistent infection should have you worried, but at least it’s not Ebola.
While most of my research is directed toward antibiotic resistance in bacteria, the vast majority of the news in the popular media suggests that the most prevalent diseases are caused by cancer and viral agents. While concerns of bacterial drug resistance are on the rise, the fear of an influenza pandemic or an ebola outbreak creates excellent headlines.
Additionally, bacteria are relatively slow killers and infections are generally treatable (although some are not). A virus may have an incubation period of about two or three weeks with mild flu-like symptoms. During this time you may believe you have acquired the seasonal flu, and that it will pass. You hug your kids, and walk around the office touching doorhandles, shaking hands, and using the company copier. By the time you’re hemmorhaging and you realize it’s not just the flu, it’s too late, and you may have infected others.
The first thing you learn in microbiology is that bacteria are ubiquitous, but these single celled organisms are not alone in their pervasiveness. There’s a saying that for each bacterial species, there exists at least one virus that is capable of infection. Viruses are extremely prevalent. In a single milliliter of sea water, there are roughly 10 million viral particles, and about 15 times as many viruses as bacteria (a fun read). Despite the prevalence of viruses, most are incapable of infecting humans. Many bacterial infections are closely associated with immunocompromised individuals, and immunosuppression is often caused by a virus, such as HIV (opportunistic infections and AIDS).
Viral research has lead to incredible advances in medicine. Because general hygiene has decreased the incidences of bacterial caused diseases such as plague and tularemia, scientific efforts have been directed toward understanding viruses. Vaccines for smallpox and polio have saved an immeasurable number of lives. Viruses may even be key to a future cure for cancer or other genetic diseases, as viruses have been engineered as tools to deliver gene therapies (an easy to read microbe wiki link on viral based gene therapies). Hopefully I can shed light on some interesting aspects of emerging infectious diseases.
*I began writing this as a brief introduction to highlight some of the research in the field of microbiology, virology and immunology. I had too much to say, and hopefully my next post will cover this paper about how ebola evades the immune response.
The best thing about science is that it does not lie. If your hypothesis is wrong, it has the balls to tell you that you’re wrong without any of the “A+ for effort” fluff. On the other hand, if you are correct, science will very subtly hint to you that you are somewhat clever in finding a solution to your question. In rare situations, the answer will be right in front of your face. Most of the time, science will tease you with hints of the next step. And always, an answer to your question will pave the way for a hundred new questions. In the end, real answers require not only a lot of work, but also a lot of luck.
Chances are that you will die of heart disease, cancer, or a stroke. But that’s just probability. After all, it was by a marvelous stroke of luck that the monkeys shipped to the US carried Reston ebolavirus rather than any of the agents that cause Ebola hemmorhagic fever. Life is a lot about luck. Science is a lot about luck.
Science is a lot like sports in a way; talent can only take you so far. The thing that separates the good from the excellent is practice. Good baseball players hit the ball well. To be a good hitter, you have to hit, and you have to hit a lot. The same goes with science. If you want to be a scientist it takes a lot of practice and repetition. If you swing the bat enough times, you’ll eventually learn the best way to hit the ball.
In sports, you hear a lot of “I do it because I love the game.” Remember, these athletes are not out there playing the game because they fell into it. They practice and play because they genuinely love the game. Sure it’s nice to make millions of dollars a year to do the thing you love doing, but is money really the driving force here? We could argue about incentives and how they’ve driven society to where it is today. We would go back and forth, and I would agree that incentives are an excellent motivator, however there is one thing I find more motivational than any incentive you can give me. And that one motivator is dopamine.
Cocaine is one helluva drug. Kidding. The cliche is as follows: “Do what you love and you won’t have to work a day in your life.” If you love getting paid to sit in a dugout for half of your salary and bake in the sun for the other half, then baseball might be for you. Of course I’m joking. Who doesn’t love a game where 11 minutes of action are injected 5 seconds at a time throughout a 3 hour period?
The takeaway is this: it’s a lot about luck. frustration is common and failure should be a giddyup. if you enjoy being wrong a lot, science and graduate school are for you.
Most researchers would be absolutely thrilled with a paper in Cell, Nature, PNAS, or Molecular Micro. Here at Oxford, those journals are the standard. The competition here is fierce, and that breeds better science. A combination of fear and prestige has lead to the University of Oxford becoming one of the best research institutes in the world. The fear of losing funding is an excellent motivator, and the title of the university means that if you don’t produce, your ass is getting kicked out the door.
While not everybody’s research will yield groundbreaking results, the general productivity of a lab can be measured by its impact factor. Of course, impact is a poor measure of scientific success. Like the SAT, GRE, and GPA, impact factor is just a number. But let’s work with the assumption that higher impact means better work. The impact factor of the labs here is incredible. Of course, there are labs around the world that are definitely comparable with respect to scientific productivity, but there’s one difference I note. These people work smarter, not harder.
I am a part of a lab where the PI routinely comes to work at around 6am, and leaves at 2pm. Perhaps it’s the balance between “work” and “play” that makes him so productive. Maybe because he knows he has a strict 8 hour work day, he does more during those hours. Maybe it’s just because he’s more intelligent. But ultimately, he has achieved a higher impact factor per hour than most researchers. He’s more efficient.
If your PI has to push you to come into the lab, or you complain about staying late, maybe you need to adopt a new philosophy. You may be more productive if you stick to a schedule. I am still under the impression that more hours in the lab mean more opportunity for success, but 12 hours/day, 7 days/week in the lab is not for everyone. To paraphrase Bill Gates, give the job to the laziest person because he/she will find the easiest way to get it done.
Take it with a giant tub of salt as I’m the last person to offer advice about life balance. If you find a job you enjoy you’ll never have to work a day in your life. Sorry, that was a lie. Every job has something you will hate doing. But you get the idea. Be efficient.
It’s pretty obvious that there isn’t enough time in the day.
Conferences tend to leave you with more questions than answers, and that’s science. With every answer, you have ten more questions. But there just isn’t enough time to investigate everything you want to know. Weird and inexplicable things happen all the time in science. Sometimes curiosity can get the best of you, and drive you on a tangent to delve deeper and deeper into a story with no apparent end. And that’s the best part.
Sadly, science funding is now in a place where curiosity is rarely funded, and translational biomedical science has the upper hand. However, curiosity is what got us here. Exhibit A: Leeuwenhoek wanted to look at little things, and with his crude hand-crafted microscopes, he did just that.
Books and their facts rarely give you an idea of what is still left to discover. Just think that each sentence in your book is the summary of a scientist’s contributions throughout his entire life. Most scientists rarely make breakthrough discoveries, and barely contribute a sentence to your book. However, their curiosity at least gives them a chance, and each mechanism that is seemingly understood just raises more questions about how or why.
But curiosity must have direction. For example, I wanted to clone a gene in a specific orientation, and without going into detail, the gel above shows 9 plasmids with incorrect orientation, and 1 correct. It is interesting that I have a 10% success given that the gene I want to clone can be inserted in only two directions, giving me a 50/50 chance of the correct orientation. This discrepancy in orientation could be due to a variety of effects, but I simply don’t have time to investigate this phenomenon, especially when all I really want is my clone.
The questions in science are the best part, and we take them for granted. Sure, you study an important protein, that when defective causes Alzheimer’s. But keep in mind the big picture. Your protein is encoded by DNA, regulated transcriptionally and translationally, and has interacting partners within the cell. All these processes, so little time. Focus, and good luck.