Name: Dean Lee (he/him)
Left PhD with a Master’s: Neuroscience, Harvard University, 2018
Disclaimer: This individual did not fully complete a PhD and chose to leave their program with a Master’s degree. We’ve included their story in PhD Paths because it still offers valuable insights into navigating the transition out of academia. Additionally, many PhD students leave their programs early, and their challenges and successes are equally important to highlight.
What was your main area of research?
I studied how neurons in the developing mammalian cortex acquire their molecular and functional identities.
What is your current job?
I am a Senior Expert I in Data Science. I am a computational biologist working mostly with omics data for Novartis in Cambridge, Massachusetts.
I analyze large-scale omics data to help advance oncology drugs to the clinic. I work mostly with bulk and single-cell RNA-seq data.
I love the autonomy. It is great to have the opportunity to use my understanding of the biological question at hand to inform which datasets I use, how I analyze them, and how to interpret the results to impact drug development decisions.
How did you find this position? What were the career steps you took to get to where you are now?
I applied for the job posting online.
PhD student ➡️ Left with a master's ➡️ learned some computational skills while working odd jobs ➡️ bioinformatics analyst in an academic lab ➡️ computational biologist in small biotech ➡️ computational biologist in large pharma
Why did you decide to not pursue a career in academia?
I really wanted to finish the PhD. But my PI had the impression that this path was not right for me. So she asked me to leave. It was very hard. I struggled with my identity afterwards for years. I wanted to continue doing science, but constantly felt that without a PhD I would never be taken seriously as a scientist. It took many years for that feeling to subside.
What advice do you have for someone getting their PhD and looking to pursue a career outside of academia?
Consider joining a lab that regularly places people in industry roles.
I used to think that being in a life science PhD program meant having full freedom to join whatever lab to study whatever topic I wanted. In retrospect, I realize that freedom is a luxury not everyone can equally afford, especially if your goal is to work in industry.
Joining a lab with super cool science yet little industry relevance comes with a degree of financial risk. If your PhD doesn't work out, how will you pay the bills? Even if it does work out, how will you pay the bills? You will have few immediate options in industry without substantial additional networking. Some students have the financial buffer to cushion this transition or to give themselves more time for their job search. Others don't.
On the other hand, joining a lab that regularly places people in industry roles comes with many advantages. Maybe the science isn't as catchy. But you will already have former labmates who now work in industry and can give you a referral. Your PI might be a scientific advisor to multiple biotechs and can give you an in. The technical skills required for your work in that lab are likely used widely in industry. Maybe you have a family member who needs help with debt or personal financial milestones you want to achieve; having more immediate access to industry jobs after graduation could matter a lot to you. Your personal financial goals shouldn't be dismissed in the name of advancing science.
What you choose to study for your life science PhD and gaining industry-relevant skills don't have to be mutually exclusive.
Start lining up your post-academia options 1-2 years in advance.
Your PIs are likely going to be woefully unhelpful in your job search, so you have to do your own career exploration.
Before I officially started looking for my first compbio job in biotech/pharma, I spent about 1.5 years reading job descriptions (JDs) on LinkedIn almost daily. I downloaded particularly attractive JDs and saved them in my Google Drive so I can study/compare them.
By the time I was ready to apply, I knew which compbio skills have sustained demand, which companies have historically hired many computational biologists, which companies are posting compbio jobs for the first time, which flavors of compbio jobs are out there, and what level of experience each title typically expects.
Having a longitudinal view of the job market helped focus my job search.