Dr. Tomas Babak, Assistant Professor, Department of Biology at Queen’s University, discusses his career trajectory from his PhD with Drs. Tim Hughes and Ben Blencowe to his industrial postdoc at Rosetta Inpharmatics to his senior scientist position at Merck, prior to returning to academia. Tomas provides insight on strategies to succeed in industry and keep doors open for academia, and his fascination with developing new technologies to address biological questions including ways in which to exploit high-throughput data sets to understand complex disorders, like schizophrenia and cancer.
Describe your career path from Molecular Genetics to your current position?
I completed my PhD in Tim Hughes’ lab, where I was co-supervised by Ben Blencowe. The Hughes lab was one of the pioneers in microarrays, and I had always been fascinated by new technologies and the application of these new technologies to biological questions.
After my PhD, I applied for a post-doc position at Rosetta Inpharmatics in Seattle, the same place where Tim had done his post-doc. It was the only position that I applied for and luckily, I really liked it so I moved to Seattle. At Rosetta, I worked on developing applications for next-generation sequencing technology, which was just starting to gain traction. Two years later, the financial crisis hit and Merck, who owned Rosetta at the time, decided to close down the facility to cut costs. They offered me a new position in Boston and I really liked what I was doing so I packed up my bags and moved to Boston. I worked at Merck for three years as a senior scientist. During that time, I built up a small research group of my own where we developed next-gen sequencing methods for other research groups at Merck.
Industry was great and I loved it, but I was starting to think about transitioning back to academia. But I knew that if I were to move back into academia, I would need to publish some papers. One of my former colleagues from Rosetta was just starting his own lab in the Department of Biology at Stanford and suggested that I work with him for a couple of years to publish some papers. At that time, my wife Sheena was looking for a post-doc and she had a great opportunity in San Francisco so we decided to move to California. After two and a half years at Stanford, I applied for and got a position at Queen’s University, which is fantastic because my family is around the Kingston area.
Can you tell us about your current research?
My lab will be 70% computational, with a focus on high-throughput data sets and how they can be applied to complex disorders, like schizophrenia and cancer. Our goal is to use transcriptomics to understand cancer and its causes. At Stanford, part of my research examined genomic imprinting, where one inherited allele is selectively silenced. You can use RNA sequencing to look at allele-specific expression and apply the same methods to understanding cis regulatory causes of cancer. Another project that I’m really excited about is trying to increase the length of sequencing reads from Illumina sequencers, which is one of the biggest challenges in the field. Currently, sequencing data is only available in short reads, so assembling them into a genome is not a trivial task.
When did you realize that you wanted to become a scientist?
For me, the realization that I really loved science came during my fourth year thesis project at Queen’s University. For the longest time, I thought that I wanted to go to medical school. In my research project, everything failed but knowing that I was the first person to try and answer a question that no one else knew the answer to – that was just really cool.
Why did you choose the University of Toronto and the Department of Molecular Genetics for your graduate studies?
I interviewed with three or four different departments and in the end, MoGen seemed like the most enabling department. MoGen had the top minds in the world, excellent resources, and the rotation system, which I really liked. It seemed like an environment where I could be creative and have the freedom to choose the research direction that I wanted to take. From a scientific perspective, I found the whole concept of high throughput methods and functional genomics to be really cool so I joined the Hughes and Blencowe labs. Both Tim and Ben gave me a lot of freedom to pursue my own scientific questions, which made the training environment especially appealing.
How did your experience in graduate school influence your career trajectory?
In my mind, the greatest objective of the PhD experience should be scientific training: skill acquisition, development of scientific thinking, and practice doing science. All of those factors were in place at MoGen. I wasn’t forced into a project and I was allowed to work on my own ideas. Even though my supervisors thought a lot of my ideas were long shots, they still let me try them. The motivation that comes from answering your own research question is enormous. When you hit a challenge, you work really hard to get through it. Ultimately, the moments when you struggle the most are also the times when you learn the most.
For me, grad school was also a time to figure out whether or not I wanted to base my entire career on science. Others see it as a place to learn valuable skills that can be applied to another career path. In grad school, I discovered that I really loved being a scientist and that I’m really motivated by answering scientific questions.
What are your favourite memories from grad school?
I was the social representative, the treasurer, and later, the GSA president. In these roles, I interacted a lot with all of the students and the professors. It was just a great collegial environment and I established friendships that remain strong to this day. The pub nights and the retreats were also pretty phenomenal.
What was the most important thing you learned in grad school?
Controls. In genomics at the time, a lot of the experiments being done were fishing expeditions and they would just publish whatever worked. For five years my supervisors and committee members insisted on doing good science, having all the right controls and really making sure that the experiment tells you what you think it is telling you. It may sound silly or obvious, but it is amazing how many colleagues I’ve interacted with to whom this wasn’t as obvious. This regimented skeptical approach has proven to be invaluable in the science that I’ve done throughout my career.
You worked in industry for a number of years, as a post-doc and as a senior scientist. How is research in an industry setting different from research in an academic setting?
Surprisingly, industry is more collaborative than academia. In academia, people collaborate with each other but it is still very individualistic. Academia is driven by a culture of papers where first and senior authors count the most. In industry, it’s not as individualistic. Everyone has a clearly defined role and the projects are very much a team effort. At the same time, having a clearly defined role is one of the downsides of industry, especially in big companies like Merck. For example, my job could be to maintain the computing cluster for a research group but that is all I would do. It almost seemed like there was a void of creative scientific thinking because no one was interested whereas in academia, you are surrounded by people who love discussing new ideas.
In industry, money dictates what is or is not worked on. If your projects align with company objectives, there are typically more resources available to you and it’s easier to obtain approval to do a big, expensive project. The downside of that is even if a project is going well, it could get cut by a superior. Sometimes, you may not even get a good explanation. However, this can also be a positive thing because if a project isn’t going well, it could just get canned, giving you the freedom to move quickly to the next project. In academia, deciding when to cut your losses and move on is a much more difficult and longer process.
After your time in industry, what drew you back to academia?
Ultimately, it was the freedom and creativity of academic research that persuaded me to leave industry. The option to work on whatever you think is worthwhile was by far the most attractive feature of academia. You still have to convince to grant review panels that it is a good idea, but I think that grant writing is actually a valuable exercise. Even if you don’t get the grants, it can be enormously educational if the feedback is constructive.
There are many different ways you could make the transition from industry to academia but at the end of the day, publications are key. You need to be in a position where you can publish papers before applying for an academic position. That was why I had to go back to being a post-doc. It was a hard decision and all of my colleagues in industry couldn’t understand why I wanted to do it. They thought that I was on track for a great career in industry and that by going to Stanford, I was taking a step back. And in some ways, it was a step back. I went from being a senior scientist with my own group to being a post-doc. That was a hard transition and it definitely affected my life-style.
You recently set up your own lab at Queen’s University. What are some of the challenges of transitioning from a post-doc to a PI?
The biggest challenge is going from a post-doc, whose main job is to do research, to a PI with 30 different roles. It’s not something that they prepare you for – you’re just thrown into it. All of a sudden, you’re an administrator; a marketing individual selling your scientific ideas; a logistics person setting up equipment and a lab; an HR person hiring students and post-docs, etc… But at the end of the day, you’re still a scientist, expected to be at the peak of your game. It’s definitely a juggling act.
What was the best advice you received when you were preparing to graduate?
Line up your next step before finishing your PhD, even if it’s a year beforehand. If you can show your committee that you’ve already secured a post-doc position or a job, they would be hard-pressed to deny you your PhD at that point. It can greatly accelerate the finishing process, which can sometimes drag on.
What advice do you have for students who want to pursue an industry postdoc or a career in industry?
Being surrounded by academics for all of your training, for whom academia was likely the best suited career path, it is easy to adopt the perspective that industry positions are a backup or a sell-out. Unless you make an effort, you rarely have the opportunity to interact with people in industry. Landing a satisfying job in industry is just as difficult as landing a PI position, so you really need to make connections as early as possible. Career fairs, co-ops and emailing investigators in industry are great ways to start. Companies are not opposed to collaborations and there are scholarships, for example from NSERC and MITACS, which are specifically designed to encourage these collaborations.
A key feature I would look for in an industry post-doc is whether or not I would have the freedom of publishing my own papers. If you can’t publish your own papers, then you are essentially closing the door on academia. But if you’re sure you want to go into industry, then that isn’t as important. There’s also a huge range of companies in industry from small biotech companies with 5 or 6 people to huge pharmaceutical companies like Merck. I would want to make sure that there’s enough funding in place for at least two to three years because that’s not always guaranteed. Make sure that this company is going to be around for a long time and get that two to three year commitment in writing. Lastly, you should interview with many companies. I only went to one interview but I don’t think that’s the best strategy. To paraphrase Steve Jobs, if you don’t like coming into work on most days, then you are probably not in the right job.