Response to a new graduate student: advice for how to to choose a lab

1. Find a really good research fit. You want to be sure that you are really into the research questions and very motivated by those questions long-term. A Ph.D. takes at least 5 years. Are the research questions going to fuel your fire at least that long? Also, it is good to understand how much independence you will have to suggest and direct the next steps in the research.

2. Pick the least evil environment when times get tough. You want to be in an environment that is going to be the least evil when research hits a wall. Think to yourself: when science is not working and things are not going well and my personal life blows up, what project and lab environment will allow me to persist, remain focused, and overcome? This may sound a bit cynical, and certainly not all of grad school will be a struggle. But, let's be honest: there are challenging times in life and research that require above all persistence, confidence, and a research environment that supports students to overcome the most common hurdles.

3. Seek out a positive advisor relationship. Your relationship with your PhD advisor is important and should not be underestimated. This person is going to write your rec letters for the rest of your life - it is a permanent relationship. You want to thoughtfully choose someone who will provide opportunities to students, who is professional and level-headed, and who will help you to get the career that you want as much as they can, no matter what that career looks like. You could ask about the career paths of recent PhD graduates to gather data on this one. Early on, be up front with your future advisor about your career goals. If s/he seems not supportive or disinterested, that is a red-flashing-light warning. At the same time, you don’t want a push-over advisor who takes all of the lost puppies - difficult or undedicated folks will drain the research program and can set a negative tone. Look at who the PI has recruited and how long/whether they stick around. Do the other students and personnel seem happy? Is it a positive work environment? Ask the potential advisor: I want an excellent letter of rec one day, what are your expectations of what I have to do to earn it?

4. Bust the myth about 100% funding. A lot of new grad students are really worried about long-term funding and want to select a lab that is flush with funds. With some exceptions, this is actually one of the more trivial aspects of a joining research lab, because hardly any PI can make an earnest financial commitment to a fully funding a student for 5+ years. As long as there are TA-ships or something else for back-up, and as long the PI has a history of funding, the current resources of a lab shouldn’t cause worry. In other words, think big picture when it comes to finances. Furthermore, it is really not a deal breaker to have to TA even as often as one semester a year - that leaves 9 months for open research productivity. It's not a dire situation. I’ve actually found that the research productivity of my students often improves when they are teaching because they get to be more efficient and productive with the time that they have. Two points: teaching isn't that bad, and you will likely be funded most of the time, or else the PI would not be recruiting.

5. Set a high bar in scientific integrity. Join a lab that has high integrity in their research. You don’t want to be a party to sloppy science, and sloppy labs can cause not only heartache but also reduce your productivity and the potential impact of your research. Imagine if you started work from an observation of someone else’s data (maybe a grad student who has just defended) and didn’t find out it that the data were suspect/bad/erroneous until 1 year in? You know the drill for identifying labs with high integrity- can you find old data? Do people keep lab notebooks? Can you find them? Does anyone check the lab notebooks? Can you find protocols? Do different folks use standard protocols or do people do whatever they feel "works"? What about sequence data and computing, how is that handled? Could you repeat someone else’s statistics if you had to? How are data stored and backed up? Can you find that reference genome or that standard library or other shared lab resources? If the answer to any of these questions is no, it may be a signal to keep looking.

6. Develop marketable skills. You want to build a sweet skill set that would support your dream job, but also are diversified and reliable in the larger market. If your Ph.D. is going to involve doing one assay over and over again, that is not a rich or marketable skill set (unless the assay is actually something to do with coding). Skills like statistical analysis, data handling, and general computing are desired no matter what is the next step after the Ph.D. Think about the science of the future, and what skills will be required to be successful, and then make sure that you have the opportunity to get really good at some of them and to become familiar with the others. Critical thinking, strong writing, and effective communication are additional skills that require investment and are extremely marketable.