Learning how to hire #2: Advice about hiring new lab members

I just went through the month-long process of hiring a first research assistant for my new lab. If navigating the posting of a position through HR was tough, what followed was even tougher. Partially thanks to Craigslist (see here), we ended up with almost 200 applications in 4 days, got them down to 10 viable candidates for phone interviews and 6 candidates for in person visits. This decision also involved dozens of phone calls to references and a lot of thinking about defining the responsibilities of the position and the required experience and how much training should be involved. Overall, it was very informative and we are really happy with our selection.

I tried to follow some of the advice I had received in the past from senior investigators (here and here) about taking my time and being mindful of my "gut feeling", but a recent series on LinkedIn from Joel Peterson, the chairman of Jet Blue, has a lot of great insight on the 10 biggest hiring mistakes.

Mistake #1: Hiring yourself. Diversity is good to bring balance to the workplace. You just want to make sure that all personalities gel together. You also cannot expect that everyone will be just like you and have to accept individual differences.

Mistake #2: Hiring too fast. Take your time hiring and finding the right person for the job. This has been repeated to me many many times by countless people. Do not rush to fill your empty lab or you will risk hemorrhaging cash and not being able to start on your best foot.

Mistake #3: Hiring the resume, not the person. Someone may look great on paper, but may not fit the culture or the energy of your lab. The first few people are incredibly important in defining the way you want your workplace to feel: vibrant and exciting? fun and relaxed? focused and ambitious? Peterson puts in terms of "brain and heart", you want someone smart and motivated, but also someone passionate about the job at hand. One more post I wrote about establishing your lab culture here.

Mistake #4: Interviewing on autopilot. Do not just go through candidates all in a row without a strategy.  I interviewed 8 people on the phone in one day and by the end of it I was completely exhausted. Because HR asked me to be consistent, I developed a script for what I was going to say about the position and for the questions I was going to ask and I took notes on all the answers, and that was my saving grace because by the end it all blended together. I took notes on qualifications, but also "gut feeling" on whether the person would be a good fit. The in-person visits were split in several different days so that we really had the time to talk to the candidates and better explore insight or inconsistencies coming from the previous chat.

Mistake #5: Lazy reference checking. Always always check multiple references ON THE PHONE and ask difficult questions if necessary. This may be by far one of the most important things. Firing people is difficult and emotional, but for some reason firing people in the lab seems sometimes impossible and is always messy. I have seen a lot of horrible situations where the fit was just not right and where information may have emerged from candidly talking to the references. During my own recent hiring, I received tons of honest feedback positive and negative which greatly informed my hiring decision.

Mistake #6: Freezing out your team. The entire team should be involved in the decision process and I may add, people should have power to veto a hiring decision. For a large (40 person) lab, my postdoc lab had an amazing combination of people who for the most part got along well, which is very rare for such a group. One of the most important features of the hiring process was that we all participated in it and talked to candidates, took them out for lunch and got to know them a bit. Everybody's opinion was considered and that was very important in making sure that only great people got in.

Mistake #7: Only hiring inside or outside. By definition in science you almost always hire from outside because people cycle through as they rise through the academic ranks. Moving around is favored and people are discouraged from remaining in their PhD lab for a postdoc. But continuity has its benefits and there are positions that may require more continuity and better knowledge of your institution.

Mistake #8. Blowing the first 90 days. This is another very important one! The way someone interacts with the team and absorbs the lab culture is dictated during their onboarding process. The culture you want them to absorb and the techniques you want them to master will become the focus of the training period and the way your new hire performs may depend on this.

Mistake #9. Focusing on money. If you wanted a high-paying job, you wouldn't be in academic science, but the lesson here is to provide rewards and positive feedback that go beyond compensation. In his great book about motivation, Drive, Dan Pink discusses Autonomy, Mastery and Purpose as important driving forces in employee motivation. See my post here for using these forces in the lab.

Mistake #10. Not firing a bad hire. Firing often seems impossible for scientists and a lot of "lab horror stories" revolve around people who should have been fired years ago (or not hired in the first place). I am not looking forward to this and I really hope it never happens, but it is so much easier for all parties involved to end things quickly and ease a transition to a different position.

Hope this is helpful. I will definitely try my best to avoid these mistakes.

A new paradigm for autism therapy from cancer research

I do not have much time to read for pleasure, but before a long flight I finally managed to pick up a copy of The Emperor of All Maladies, Siddartha Mukherjee's Pulitzer-prize winning "biography of cancer". The book is masterfully written and absolutely mesmerizing, but it is not my goal to review it here, as more poignant reviews were penned 3 years ago when it was first published.

As a scientist one of the most fascinating things is to follow the process of discovery: see what physicians and scientists inferred from what they saw and how they came to often very wrong conclusions with the very best intentions, how ideas became fixed in the common knowledge and how revolutionary approaches came to be. Like the organisms and molecules it studies, medical science is constantly evolving and ways for looking at scientific problems with new eyes are always necessary.

One thing that struck me of the evolution of the thinking about cancer, is the fact that at first we did not know that the same name encompasses multiple different disorders and the common approach was to find a cure-all drug that would work on everyone. After much often devastating trial and error, we now known specific drug regimens may only work on a specific form of cancer. Cancer is in fact becoming the poster-child for personalized medicine, an approach requiring a specific understanding of the individual patient's and tumor's history and genetic makeup. The rationale is that each type of cancer and maybe each individual cancer is different and the hope is that once we figure out what makes each tumor explode in millions of proliferating cells, we may be able to design a tailored regimen to stop it.

Reading about those initial struggles on how to deal with a very heterogeneous disorder that yet often looks similar in many patients, made me thing about the changing concept of autism nowadays. The herculean genetic efforts of the past few years have determined that autism is not caused by common genetic changes, but it is more likely due to a single faulty gene in each case. The rub is that the mutated gene could be one of dozens or hundreds, and as many clinicians and parents may tell you, each affected child may need to be considered as a unique presentation of the disease. This confusion is reflected in the recent changes to diagnostic criteria listed in the latest version of the Diagnostic and Statistical Manual of Mental Disorders or DSM-5, which groups all autistic-like symptoms of different severity under the term Autism Spectrum Disorders (ASD). So, is it one big disease or hundreds of different ones that we cannot diagnose individually? Is there a miracle drug which will work on everyone in the spectrum or do we need to figure out a way to group patients with defects in similar molecular processes, or even treat everyone differently?

Some food for thought came from the recent demise of arbaclofen, an experimental drug for autistic behavior in individuals affected by Fragile X Syndrome. Fragile X Syndrome is a common cause of intellectual disability and is often associated with autistic features, but as in all forms of ASD the symptoms and the behavioral problems are greatly variable. As described in a New York Times article last month, arbaclofen was deemed a failure after it showed no affect on a phase 3 clinical trial and funding was pulled. Yet a small number of patients showed remarkable improvement in their social interactions and parents are desperate that they will now lose access to the drug. It is possible that arbaclofen may only be effective in a specific subset of cases and that other patients may need different drugs. It is also possible that the children who responded well to arbaclofen may have improved on their own or responded to anything, but we will never know if we do not test these conflicting hypotheses. If there is a "type" of autism that responds well to a specific drug, it may possible to discover more types and their treatment, as is being done for cancer.

Learning how to hire #1: Find your Research Assistant on Craigslist

I need to hire a Research Assistant either with a very specific attitude or set of skills, so I wrote a somewhat detailed job description and hoped for the best. But where to get access to a lot of applicants? My postdoc lab had recently hired an RA, advertised on Craigslist and got 90 applications, but since I was not involved in that hiring and I do not have a big HHMI lab, I was somewhat skeptical of how many people would apply to my lab.

At the same time just advertising on the Jobs listings of my institution may not be enough to reach a wide audience. I perused biotech/science job listings on Craigslist and when I saw that the Library of Congress advertises there I was sold. The listings are sparse, but that may not be a bad thing and there were not any recent academic RA jobs posted. The listing cost $25 which is a pittance compared to what postdoc listings cost on professional organization websites.

Lo and behold I posted the job on Friday afternoon at 5pm and I had more than 100 applications in 3 days with peaks on Monday morning of one application every 20 minutes. After discarding applications from candidates with no experience or qualifications in other fields, I had a pool of a few dozen people who looked interesting. Then, after combing through another 50+ applications from HR, I had multiple candidates with some combination of the required set of skills and experience. We had so many applications we had to shut down the listings after 4 days because going through them all would become unmanageable. Interestingly, the two applicant pools were almost completely separate as only a few people applied through both systems, so Craigslist was great for diversification. In both cases I had more and less experienced applicants and a similar distribution of ages. And now the phone interviews begin...as far as I'm concerned, the Craigslist experiment was a success.

Never pay retail....in the lab

I am an avid shopper and I love nice things, but as a grad student and postdoc I didn't have much
money, so I've become an expert on where to find the best bargain and how to wait for the things I wanted until I could get the most favorable price. I doubt it's safe to buy lab supplies on eBay (though there are quite a few things available), but in a few months of running a lab I discovered that the "never pay retail" rule is also true for labs.

Every new principal investigator (PI) knows about the new lab discounts you can get from multiple companies, but what I didn't know is that you should never be satisfied with those and that you can get discounts all the time....for almost everything. You just need to ask, and better you need to come armed with quotes from multiple companies and from pricing that was extended to other PIs. I have quite a few friends that have started labs in the past couple of years plus multiple people at my new institution, so I've been collecting quotes and deals from everyone. Then I can go to the different vendors and get quotes and pit them against each other and against the best prices I have heard of. This is time consuming and it is sometimes uncomfortable since you may develop a rapport with certain vendors and you may be genuinely torn between different products, but the dance is worth your time. If a company offers 30% off and you like another product better, you should ask the competing company to extend the same discount. Everything is ridiculously expensive and your start-up money is very precious.

Some things I've learned:
- If you are in the market for a good microscope and have found one you like, ask whether demos are available. Demo microscopes are just lightly used and you can get a better price for what you want or some free bells and whistles which could become handy.

- Always see if you can get free reagents/consumables with your equipment purchase and if you get a $1000 ask for a quote for what you need with the new lab discount and get even more stuff for free.

- Find out if your institution allows you to purchase your fridges and freezer for a regular stores. Best Buy will have freezer for a fraction of the price of big distributors like VWR or Fisher and you can find deli case fridges from restaurant supply stores at half to a third of the price. Google "2 door beverage merchandisers" and you'll see.

- The price of chemicals may vary wildly and one friend recommended to always double check since she level of purity does not necessarily make something more expensive. Companies will make the most requested item the cheapest, so you may be able to get a better purity for a smaller price tag.

- Always always ask for a better discount....and always ask around for what your friends and colleagues are doing. What was the norm in your old lab could be done with alternative approaches that are much cheaper and there may be other things you want to splurge on.

Every little bit counts.

Self-sabotage in academia: tips on what not to do

A friend recently posted a great article from The Chronicle of Higher Education on "Self-Sabotage in the Academic Career", which points out 15 ways you can hurt your career during the tenure process. The article is applicable to any tenure-track position whether in science or the humanities and you should just read it. While asking for advice from senior investigators in the past few months, I had already received some of these tips (here and here), but it's worth keep repeating them, since they come up over and over again.

These are the ways to be self-destructive:

In your field:
You don't seek out multiple mentors.
You don't seek out external evaluations.
You aren't well known outside your institution.

In your institution:

You pay too much attention to personal relationships - or too little.
You fail to understand the cultural norms of your institution.
You have been involved in one too many departmental squabbles.
You are too selfish or too selfless.

In your research:
You are either perfectionist or perfunctory in putting your work into print.
You hold on to revisions too long or rush them out.
You lack resilience in the face of failure.
You got stuck in your dissertation paradigm.
You collaborate too much with colleagues from graduate school or your postdoctoral years.
You fail to have a coherent research plan.
You haven't figured out who you are.
You are guilty of any kind of academic dishonesty.

In summary, innovation, independence and collegiality are things to strive toward while identifying as many mentors as possible to help you through.

A spectrum of mental health disorders

I have written a lot of about management and grants and lab equipment, but I have not written much about science. I was trying to keep the blog consistent, but the nature of the internet is not linear: readers come in and leave at any point on anything their web browser selected for them. I usually talk about science with colleagues and friends, but it may also make sense to repost some interesting findings or discussion points.

An issue very close to my heart is the study of mental illness, which is what I do. A few weeks ago I was discussing autism with a foundation and I was asked whether I believe that autism is a mental illness. I found it an odd question. "Of course autism is a mental illness" I replied "it is diagnosed according to the DSM, the Diagnostic and Statistical Manual of Mental Disorders. What else is it supposed to be?" Clinically, by definition autism is a mental illness because it is a change in brain function which severely disrupts behavior and life, and it is a psychiatric disorder. It is a disorder, like many other disorders of other parts of the body, but mental illness still carries a different kind of stigma it shouldn't carry (which could be a discussion to have in another post).

I was looking at a recent editorial on the journal Nature, Mental health: On the spectrum, which  discusses the imminent publication of the new edition of the DSM, the DSM-5, and talks about what is a mental illness and how different disorders relate to each other. The piece describes how the diagnosis of psychiatric disorders in the past 60 years has changed and on how research has modified the way medicine approaches the problem. It also proposes that multiple mental disorders from intellectual disability to OCD, may lie on a continuum, a clinical spectrum without the clear boundaries defined by the diagnostic textbooks. I am a strong proponent of the spectrum view, but clinically you want to group cases that look the same together so that you can draw some conclusions. Yet, the genetics of mental disorders has shown that reality is much more complicated. The editorial is a very good read and food for thought.

Qiagen Finder 45-pathway Cignal array: the good, the bad and the ugly

I am still not sure whether this is going to be a good review or a bad review. It may shake out one way or another as I write it.

We do a lot of signaling as we work on a intracellular signaling scaffold which functions in a lot of different pathways, so I always pay attention to new email from SABiosciences/Qiagen on their new PCR and luciferase arrays. Upon reading about it the Cignal Finder 45-pathway array seemed to provide an awesome way to apply very sensitive luciferase assays to test 45 pathways in a single shot.
It is a 96 well plate with 45 reporters in duplicates and 3 positive and negative controls that you can use to test you drug, siRNA, over expression plasmid on your cell line of choice. The protocol is simple and straightforward: the DNA is in the wells, you add the cells and transfection reagent and the next day you test for luciferase and renilla activity. At $1,600 for a 10 plate pack, plus dual-luciferase assay reagents, it can run around $200-300 per plate, which in triplicates for 2 conditions can be almost $2,000 per experiment. But screening 45-pathways at once could be totally worth it and SABiosciences always run some kind of deal on the plates (and you can use a fraction of the luciferase reagent recommended in the Promega protocol).

We know our protein of interest would really strongly activate NF-kappaB and we have done it with a different reporter, so that was our positive control. The first plate was amazing! There were very clear difference between reporters, the duplicates looked very consistent and a whole bunch of interesting pathways lit up in addition to NF-kappaB in our experimental condition. The dynamic range of response was incredible with some reporters with intensity in the 2,000,000 intensity units and some in the 2,000. And so we embarked in a huge study with over expression and siRNA...and ordered another 10-pack. Qiagen provided us with a handy Excel file for analysis where we just needed to plug the results of luciferase and renilla for each plate and everything would be calculated and plotted for us.

I was intrigued by some of the results and started paying a lot of attention to the intensity measurements, and that is when things started getting ugly. We had noticed that some of the duplicates were asymmetric in intensity when a low intensity reporter was next to a very high intensity one. I had had similar problems in the past with white plates in our luminometer, where we noticed spillover of fluorescence in neighboring wells. Some people say it's the fluorescence passing trough the white walls, others that the detector is far from the plate and the fluorescence spills over from above like a halo. Also instead of looking at the results in the Qiagen spreadsheet where they are in linear format, I analyzed everything in plate format, where I could see which well was above, below, left and right of any particular reporter. That is when half of our hits became uninterpretable because they could simply be due to spillover from the strong hit next door. Qiagen recommended to half the amount of lysate, but that didn't help much as the results were basically identical. So we were stuck with the option of spending $500 per troubleshooting attempt or find some other solution....

They said it must be our luminometer, which is a possibility, but that's the machine we have in the department and their product should work even for older machines. They gave us 2 plates for free for testing, which was nice, but still leaves for $500 per troubleshooting for each one of the other variables (machine, reagents, lysate amount). Right now I am faced with a conundrum: I have some data I believe from the array and some data I do not believe, which I think is due to spillover. I cannot publish the whole array because I would have to explain it is a problematic product and I have requested for a sample of the 6-8 reporters that are iffy, but I was told I had to buy them individually, which I am not inclined to do at this time, since I do not want to waste my grant money to troubleshoot their product for them.

At the same time, their reporters work beautifully and the data we have is very robust, though for us it was more a 30-pathway array than a 45-pathway because of the issues.....I am open to suggestions from other people who may have tried the product and who may have other ideas. Also, I am not entirely satisfied with the way they recommend to analyze the reporters and I'd love input on that also.

Advance planning: the benefits of the 0, 18 or 60 month plans

As I start the lab I am trying to figure out where things are going to go in the future and come up with a career development plan. The information on career planning out there is varied and I picked a few suggestions I like.

A 60-month plan. I have been reading a great blog called The Professor Is In, which is run by a former college professor turned career advisor for younger academics. Even if you do not hire her for her services, the blog is great and it covers everything from career planning to what to wear for an interview to how to network. The Professor firmly supports a need for a 5-year plan, nicely structured month by month in an Excel spreadsheet where you identify all the deadlines you are planning to meet. This is not your run of the mill 5-year plan where you daydream about where you want to be in 5 years, this is a place where you can write down grant deadlines, conference deadlines, paper deadlines for years in advance and foresee what you are going to do March 15th two years from now. I am a compulsive planner and list maker, so the 5-year plan spreadsheet was very appealing to me. Grant deadlines are similar from year to year and conferences are planned years in advance, so after a few Google searches I had a nice detailed plan for the first 5 years of the lab. While I think this is great, since it forced me to look for a lot of grant sources and integrate my current plan for publications with grant deadlines, none of this may ever happen, as the plan keeps changing on me, so in the framework of a 5-year plan shorter plans may be in order.

An 18-month plan. I just finished reading Sheryl Sandberg's book Lean In. I have been a long-term Sandberg's fan and followed some of her advice, but this is another story for another post. In Lean In she proposes an 18-month plan, which is not as short as 1 year, but not as daunting as 2 years. The goal is to set an 18-month deadline for improvement or career development: you can either want to develop a skill, enter a new field, set a deadline for funding or publication of a particular project, develop a course. In her formulation, this is not as detailed as having a monthly spreadsheet, but it could also be used as a shorter version of the 5-year plan by planning actual deadlines for only one and a half year at a time, while keeping in mind longer terms obligations, such as when you are supposed to teach for a semester or when you are going up for tenure.

A 0 to 6-month plan. Finally there is who says that planning is futile, that your research will change completely and that your deadlines will fluctuate. I have heard from a few friends that within a year of starting your lab, your goals may have changes completely because the science took unexpected turns, and all the detailed experiment you had planned are not happening. Writing a particular grant may be postponed and other interesting deadlined may come up randomly following a friend's suggestion. Maybe a shorter 3-6 month plan is more realistic and you need to just think in the shorter term to hit specific deadlines without feeling the overwhelming weight of the future. Somewhat like being on a diet where losing 5 lbs in the short term is much less daunting than setting out to lose 30 lbs.

All three options have their pros and cons. I respond well to detailed long-term planning, but at the same time, I am very flexible when the plans do not go the way I planned. Someone who gets discouraged if plans are not kept, may find detailed long-term planning depressing and may prefer the 3-6 month timeline. Overall, I think a combination of the three may be possible with a detailed 6-month plan, a looser but definitive 18-month plan and general broad stroke plan between month 19 and 60. Maybe it's time to revise my 5-year plan spreadsheet and see how it goes.

More advice to a young investigator: lab management tips

As I was preparing to start this new adventure of running a lab, I have been collecting more and moretips post has been very popular, I thought I'd follow up with some of the new advice I have received.
advice from senior investigators, and since the previous

1) DON'T BE A PERFECTIONIST:  To get your first grants you need to show productivity and you just need to publish nice solid papers. Do not hold on to a project until you think it's perfect because it may slow you down too much. In the race against the tenure clock, this may be a good thing to remember.

2) DON'T BE AFRAID TO BRANCH OUT TO FIELDS YOU DO NOT KNOW: I have already talked about the fear of branching out to a new field and I received this piece of advice right when I was afraid. You have no idea what your career path is going to be like and you never know when the next cool project in the lab is coming from. It could be a conversation over drinks at a conference or just because you want to do things with a friend. You prospective and your expertise may just provide the fresh set of eyes the new field needs.

In addition to the more philosophical scientific suggestions, I also received several practical tips, which are really important as I am thinking whom to hire and how to manage money.

3) WHEN YOU INTERVIEW LISTEN TO YOUR GUTS AND WATCH FOR RED FLAGS: Everyone has heard about the tech or postdoc from Hell, the person who can sink tens of thousand of dollars of reagents in a dead end project, or the person who disrupts the mojo in the lab so badly to make everyone upset. Nobody has a sure fire method to avoid finding yourself in that type of situation, but paying close attention to the red flags during the interview and bringing in as many senior and trusted people as possible to judge the candidate can help. And in addition,

4) ALWAYS CHECK REFERENCES BY PHONE: References are very important and they can tell you a lot about a person. Though I've only hired a few people in my life, I have always had very informative conversation with the referees and have made hiring decisions based on their opinion. So I was not surprised when I was getting this type of advice over and over again. Some people will be very candid and give you a prospective on the applicant you could not get any other way.

5) PAY CLOSE ATTENTION TO YOUR NIH EFFORT: This is a very technical one and may only be applicable if you have a career development award, but you have to be very careful of what the restrictions are on your NIH effort. It does not make sense to spend a lot of time and sweat to apply for a lot of NIH grants, if you cannot actually spare the necessary effort, since you may have to give up the grant or part of the grant. You have to figure out with your budget people and if necessary with your Program Officer what you can and cannot do even before you apply.

6) BE WARY OF LARGE SALARIES and 7) HIRE A GOOD LAB MANAGER: Two contrasting schools of thought. Should you or should you not blow a large amount of your personnel budget on a good lab manager. Everyone who went that route absolutely swears by it saying that it was the best thing they ever did. People who did not hire a lab manager, seem perfectly happy and said they like having the extra money. What is a new PI to do?

Developing a vision and mission statement for your lab

One of my former bosses always said that running a lab is a lot like running a small business: your research is your product and you have to obtain seed funding to get your work started and continued funding to maintain production, you must advertise so that other scientists and the public know and share your research, and you have to hire and motivate the right employees. In line with setting up your culture, you also need a vision and a mission at the beginning. Who are you? What do you do?
A friend once told me that you have to be able to identify yourself in a couple of words, like a superhero name, and that stuck with me. She was Autophagy Girl, I want to be Extracellular Matrix Girl. That should be what other scientists think of you when they are looking for a collaborator or an opinion on something. What is your focus? And what do you want to be known for? When I joined my postdoc lab, my boss had an idea in his head of what he needed me for, which was not exactly aligned with what I wanted to do. It took six months to realign his expectations: "Yes, we can do that, but I really want to do this."

All universities and hospitals have mottos and mission statements and many are launching major rebranding campaign to define how they want to be perceived in the public opinion. I find quite a few labs also have mission statement and I like the idea of incorporating the goals for our culture in the statement. You always start your talks about what you are about, but what do you stand for? We stand for integrity and communication and innovation, and that needs to be made clear to the people wanting to work for me because I do not always remember to state my core values. I know that people learn by example and that you have to live your values yourself, but it also makes sense to communicate it to them clearly, so that everyone knows what the expectations are.

After looking around for a while I found a handy guide on developing a mission statement. Hope it is useful.

Image credit: By Vegas Bleeds Neon (Own work)

To the aspiring scientists out there

Tomorrow I start the job I have been working towards for the past 15 years and I have been dreaming of since middle school. I always wanted to be a scientist and when I first joined a lab as an undergrad, I decided I wanted to run my own lab. I have had wonderful times and truly terrible times, when I have teetered on the edge of dropping out of college to man the cashier at a supermarket, dropping out of grad school to go write movies or just simply hide under a rock, leaving my postdoc to go work as a scientific consultant in finance or a policy advisor. For years every day I would wake up and think "Will I quit today?", and then I would chose my job as an aspiring academic scientist above anything else. Every day.
And then, as I was interviewing for positions, something snapped into place. I truly loved the interview process. I loved talking to people about science all day, sharing my work, developing my scientific program and most of all, I loved the image of my lab which was forming in my head. Kind if when you imagine the face of your future baby and you are filled with joy. One day I was ogling the different scientific positions LinkedIn was throwing my way and the next I was set on a course to start plotting all my R01s.
I can honestly say that since getting my job I have had the best year of my life. Hiring people, buying equipment, shaping my thinking as a leader, networking like crazy have all been fascinating and exciting. It was that wonderful time when you are still protected in your postdoc lab, blessed with lots of my own funding to spend, and trying things out with training wheels. A time when you can enjoy and imagine what is coming without really worrying about it.
Tomorrow the training wheels come off. Tomorrow we begin to worry. Starting tomorrow I have 3 years to come up with substantial NIH funding and the clock starts ticking to March 31 2016. Considering how fast these past 6 months have flown, and that setting up everything in the lab may take another 6-9 months, and that I'm trying to finish three papers, and that there are multiple grants due this summer, the future is uncertain. Yet, I'm still excited and hopeful and happy to start this adventure. I am living my dream. At the same time, I have a lot of grad school friends who have not chosen this career and have gone to do a lot of fascinating things in other professions. And that comforts me, because I see that they are happy and successful, and if the NIH continues with this crazy run and funding doesn't come, I will be okay no matter what.
So, to you, aspiring scientists out there, most of all learn to believe in yourselves. Figure out what you want to do in life and plan for it, develop it, grow into it. A job, any job rarely falls in your lap, no matter if it's in academia or outside. In the lab look for your anchor, the one place or one experiment that makes everything alright, no matter what (for me it's at the microscope, looking at cells; I have friends who clone when they are stressed...go figure). My anchor tells me that I need to be there and nowhere else. And finally, if you do something you really enjoy, it will come through when you talk to people about it and maybe they will see how cool it is. So far this transition is great fun, more fun than I ever thought it would be, so know that there is light at the end of the tunnel.

You need an assistant, but don't have one: apps for travel and organization

Nowadays sometimes there is so much to do, that I don't have the time to think, let alone get organized in my life. There are days when I would really love to have an assistant. Since I do not have the money for an assistant, while trying to keep it all together, I looked for the next best thing....apps and websites.

When I travel my new best friend is Tripit (http://www.tripit.com). It checks your email for you for trip reservations (flights, hotels, buses, you name it) and nicely organizes everything. It even calculates the trip between the airport and your hotel and maps it for you. You can input the location of meetings and it will show you where those are also and it will tell you by when you need to check out of the hotel to get to the airport on time. The smartphone and iPad apps are great and have all information you need right at your fingertips, so that you don't have to fish around for pieces of paper or email to figure out where you are going. If you need to coordinate with other people you can just email Tripit their plans and it will include them. I'm moderately addicted to the Stats where you can keep track of miles traveled and cities visited. I logged more than 60,000 miles last year.

When I'm looking for the best and cheapest options for flights, I just discovered Hipmunk (www.hipmunk.com), a great site with a very nice visual interface organizing flights based on price, stops, times or "agony", which is a fun algorithm computing stops, layovers and price and deciding which flight would be less painful for you. On shorter routes, it even inserts the Amtrak timetable and price so that you can decide whether a train would be preferable. Then to watch fares, I still use Yapta (http://www.yapta.com), which I have used for years as it was recommended by multiple travel sites. You pick the flight and the airlines you want and then you watch them. Every time the price drops you get an email, and after you purchase the site still tracks the flight for refunds in case the price drops even more.

For conference expenses, I discovered ExpenseCloud (https://www.expensecloud.com), a site (and apps) to keep track for all receipts. You email registrations and travel receipts to the website and upload pictures of any random receipt on your smartphone and the site organizes a report. If you are in a company that actually uses ExpenseCloud then you would just need to send it out for approval, but even having all the numbers together in a neat report without having to organize and find all the receipts is really helpful.

Finally for everything else there is TaskRabbit (https://www.TaskRabbit.com) where you can pay someone to do stuff for you: go get your groceries, help you find a new apartment, bake cookies, organize your bills, you name it. You post your task and your target price or let people make a bid, and you'll likely have a host of TaskRabbits ready to work for you. Virtual tasks are available from everywhere, in person tasks are only in New York, Boston, LA, SF Bay Area, Portland OR, Chicago, Seattle, Austin and San Antonio. One friend was wondering whether they'll count synapses...I haven't asked, yet.

Hope this helps some overworked scientists.

Image: By Aaron Logan (from http://www.lightmatter.net/gallery/albums.php), via Wikimedia Commons

You can't succeed in science without mentors

Mentors are necessary for any type of career development (Where would you go if nobody recognized your talents and cultivated them?), but even more so in science where you need people to believe in you, give you money to develop your own ideas, trust your judgement and abilities, pretty much starting from the day you step into a lab as an undergraduate. A lot of effort is put by the NIH and other institutions to  have Mentored Career Development awards like the K99, K01, etc (see links, here), however mentoring is not uniform across laboratories and it is completely dependent on the Principal Investigator (PI). When you write a mentoring plan for one if these grants you have to describe a Utopian situation in which you constantly meet with your PI who will steadily guide you every step of the way through your projects, your papers and your career. In reality things can be quite different: your PI may not have time, may not be guiding type or only have insight on some aspects of what you do, and in the worst case scenario may actually undermine you. I have had my ups and downs, but I have been lucky (or picky) to have the mentors I needed for me at every step of my career. I've heard horror stories and wonderful stories from others.

I think the important thing is to always looks for mentors and to realize how important mentoring is. I know that people say that women always underestimate their own abilities and give credit to their circumstances without extolling their own achievements, BUT mentors were incredibly important in shaping my career trajectory. Every mentor had strengths and weaknesses, but there were multiple other mentors around me (colleagues, friends, other professors) I could rely on. While setting up my Individual Development Plan (myIDP, here), not only I had to think who my mentors are, but what they are for and it was a very interesting exercise. Instead of putting the burden of "full service" mentoring on only one person, it may be more effective to identify what each mentor is good at and use multiple mentors for all your needs. For example, a mentor for a specific part of a project, a mentor for departmental diplomacy, a mentor for grant writing, etc. As part of my K99 application I was requested to establish a Job Search Advisory Committee, a group of PIs young and older who would help me in shaping my application and navigate the interview process. Everyone of them contributed in a very important yet different way and I was a real eye-opener. Anyone can be a mentor even if just for 10 minutes, so started just asking any PI I meet for a piece or two of advice on how to set up a lab and got lots of great info.

The thing is that you will always need mentors: you will need letters from people for the rest of your life, for every career development grant application, for your tenure, for your promotion to full professor, for awards. My advice to graduate students is always that you should find at least a very strong mentor in your career, someone who will be there for you and support you and promote you and talk you off ledges whenever necessary. Having a good mentor makes your life much easier, but a lot of mentors are even better.

On the fear of branching out into a new field

This has been an exciting and emotional week. I am venturing into a new field in biology and I decided to attend a small specialized conference on the topic. I am still trying to determine in my head which projects are going to be the best bets for the new lab and I thought I could look for collaborators to help me branch out.

It is always difficult to go to a conference on your own, but it is even harder to go to a conference in a field you do not know where you know absolutely no one. I am no shrinking violet, but the constant level of attention you need to maintain and the pleasantness can be exhausting. You are trying to figure out who the leaders in the field are, who the movers and shakers are and which topics are trending, while trying to understand exactly what everyone is talking about. I'm at the top of my game with genetics and cell biology, but here surrounded by biochemists, structural biologists and biophysicists I often found myself smiling an empty smile. It had been a long time since I had felt this ignorant...

Overall, I think it went exceptionally well, I was kind of adopted by the best possible collaborators, I was invited to give several talks, I was made privy to interesting unpublished ideas and plans which will help me with directing my projects, yet I feel tired and deflated, and completely out of my depth.
It is easy to do what we know, to feel confident of our expertise, and after you spend so many years to become an expert, it can be daunting to feel like a rookie again. Yet, in chatting with established investigators and asking for advice as I usually do, a picked up a new piece of wisdom: "Don't be afraid to branch out to a topic you don't know". At dinner with one of the movers and shakers I was trying to meet, he told me about his career path and how being at the right place with the right expertise can make you able to answer very exciting questions in a new field.

I guess I have to take this advice and tell myself that I can now rely on people who have the expertise to help me. I need to build on the very valuable contacts I have made during this week.

Image credit: The road not taken by Harvey Robinson via Wikimedia Commons

Pros and cons of new K99/R00 regulations

Lat month the NIH announced some changes to the K99/R00 Pathway to Independence Award guidelines (NOT-OD-13-034), as a results of recommendations of the Biomedical Workforce Task Force. A major change is the lowering of the deadline for application from 5 years from obtaining your PhD to 4 years, which has been very upsetting to many. The Task Force was composed of several deans, department chairs and university presidents (roster) and their goal was to "develop a model for a sustainable and diverse U.S. biomedical research workforce that can inform decisions about training the optimal number of people for the appropriate types of positions".  A recent blog post from Sally Rockey, the NIH Deputy Director for Extramural Funding, also a member of the Task Force, discusses the impetus behind the deadline reduction: the goal is to emphasize mentoring, promote earlier exit from the postdoc and it is supposed to be accompanied by an increase in the number of awards to achieve a 30% success rate (here). The problem is how this is going to be implemented.

As I was applying for my K99 3 years ago, I chatted with people who had served on study sections and heard that there was widespread confusion on how to judge these awards. In going through an initial submission and resubmission and discussing with other awardees, it was clear that you pretty much had to be able to go on the job market right away. You had to provide a plan for your job search and your overall goals for your lab and you had to assemble a Job Search Advisory Committee. There was still substantial emphasis on mentoring, since you had to justify why you needed 2 more years of training, but the idea is that now mentoring will be even more important. But considering that an application with a resubmission takes one year, the timing becomes critical. You basically have to figure out what you want to write in your application during the 2nd year if your postdoc, apply at the beginning of your 3rd year and if necessary resubmit 6 months later. This is a tall order since most people do not have a well defined project until later in their postdoc and do not necessarily have a project that they can take with them. If you change fields and do a postdoc on a different topic from your PhD you may still be learning in year 2. If you are making a mouse line, you'll be at the beginning of characterization with no clear idea of what to write about. So you are left with abandoning the idea of a resubmission and just putting all your eggs in one basket applying only once. In addition, there is the issue of penalizing fellows who decide to take on a high risk project and develop new techniques, who may be troubleshooting for a few years before a big break.

I personally thought that the K99 was timed perfectly, kicking in when the early fellowships were ending and providing a cushion for the last 1-2 years of postdoctoral work. I had several friends who were blindsided by the 5 year deadline and could not make it on time despite having very exciting projects in development. I was able to take an additional year after securing my position to finish up a paper and I have been able to use the money for some really cool and pretty expensive experiments which will build the basis of the first couple of years in my own lab. It has been a huge blessing and I am a little scared for the transition to the new guidelines. I am trying to make sure all the younger postdocs know that they have to start thinking about this right away...it is just very hard when the first year is often spent reading and starting and stopping multiple possible projects.