Envisioning a computational biology talent pipeline for biotech/pharma
An ideal talent pipeline would produce job seekers whose skills line up perfectly with the employers' needs, bullet point for bullet point. When training programs, job seekers, and employers work together, it is possible to achieve this skills-to-needs alignment. Trade schools do this well. A trade school student could acquire the skill of elevator maintenance, which aligns exactly what the employers need: someone to maintain their elevators.
With this ideal talent pipeline, everyone benefits. The trade school's programs are in high demand. The students are only paying for training that directly helps them get a job. And the employers have a ready pool of qualified talent to hire from.
I work as a computational biologist in biotech/pharma, and I think our talent pipeline could be more robust. Below, I envision what an ideal talent pipeline might look like for computational biology (compbio) roles in biotech/pharma. A successful pipeline would require active contribution from three parties: universities, trainees/students, and industry computational biologists.
Universities
Universities sit at the beginning of the talent pipeline and wield considerable influence in how aspiring computational biologists are prepared.
Universities that offer PhD programs in computational biology produce people who are usually well-equipped for industry compbio roles. There are just not enough of them. Since it is unlikely to dramatically expand the number of PhDs offered in this field, we need other streams of talent, which could come from bachelor's and master's programs.
Many universities now offer bachelor's or master's programs in computational biology, in addition to many other STEM subjects that also train students to be strong quantitative thinkers. Because the field is still relatively young and changing so rapidly from year to year, instructors should update their course content every year to make sure their courses don't become obsolete. To do so, universities need to maintain frequent contact with industry professionals to reassess industry needs and update their curriculum accordingly. If that is done, then our compbio talent pipeline is mostly secure.
Trainees/Students
All undergraduate and graduate STEM students have the potential to join this compbio talent pipeline. Biology, statistics, computer science, data science, engineering, math, chemistry, and physics students with sufficiently developed quantitative reasoning can all do meaningful compbio work. That's a lot of people to feed our pipeline.
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Especially since the pandemic, in which biotech/pharma demonstrated its value to the world, interest in compbio work has grown. That also bodes well for our pipeline.
But interest alone is not enough to get trainees into industry compbio roles. We leak talent from the pipeline when trainees don't pay close attention to the ever-changing requirements for industry compbio roles. If your program isn't helping you follow these industry requirements, it is up to you to identify those requirements and fight to get the relevant skills. Don't assume someone else will do this for you. If many more STEM students can do this job market surveillance work, it will also strengthen our talent pipeline.
Industry Computational Biologists
Computational biologists currently employed in the biotech/pharma industry are at the receiving end of the pipeline, and we are the group with the most power to influence how well this pipeline works.
We could communicate frequently with universities to clarify skills that their students should acquire while in training. We can describe what the interview process emphasizes so job seekers can better prepare for it. We could craft more entry-level roles. We can also remove barriers to entry, such as credentialism and certain hiring practices. And we can definite mentor more trainees. If we can put in this work, we will have a stronger compbio talent pipeline.
We Can All Win
Each of the three relevant parties - universities, trainees/students, and industry computational biologists - have an opportunity to make changes that will strengthen our compbio talent pipeline. When that skills-to-needs alignment is achieved, we all win.
I will dedicate more articles to explore the topics mentioned here in greater detail. Stay tuned.
Bioinformatics | Writer | Explorer
7 个月This is extremely insightful! I am studying Msc Bioinformatics and I want to join industry research in this area. However, it is often tough to envision what positions I could hold or apply for in companies since most of the ads focus on sales or marketing. Elsewhere they are all termed under research. Articles like these will help someone like me navigate the field better! Thank you for writing about it.
Computational & Systems Biology | Microbiology | High throughput Data Analytics
8 个月Interesting piece Dean. Mentorship is really important, the field is really fast paced and can be really challenging for noobs to catch up. Looking forward to articles on your approach/experiences to mentorship
STEM | Students | Teacher | Experiential Education | Motivated to Network
9 个月Barbara P. Vanecia Harrison-Sanders, MSHR Michael Conte M.Ed. CSP Alex Susienka
PhD Student in Computational biology (Cancer vaccine & immunotherapy discovery) at International Centre for Cancer Vaccine Science, University of Gdansk
9 个月This is a well-written article, Dean and I look forward to the others in this series. They would certainly benefit bioinformatics graduates looking to enter the industry in the near future. As a supplement, could you also perhaps share either your or some of your peer's interview experiences at any of the major pharma companies? Thanks again!
Generalist @ longevity biotech.
9 个月Nice introductory article! I'd be curious to see what are some ways in which one can get feedback and impressions from all three parties and integrate them most efficiently. What's even better, this pipeline seems to apply to many emerging fields, comp bio being just one of them.