Bioinformatics: Academia vs Industry
In this blog post, we will discuss the differences between working in a bioinformatics role in academia vs industry. As a Bioinformatics Scientist who has worked in both academia and industry, I will use both my personal experience as well as published data to shed light on how the two compare. The main topics we will cover are: (1) work environment, (2) funding & collaboration, (3) career paths, and (4) pay & other compensation.
First, let's define what we mean when we say academia and industry.
The first comparison we will look at is the work environment. In industry, bioinformatics professionals work in a fast-paced environment with a focus on delivering practical results. There are constant deadlines that need to be met and with this can come added stress and sometimes the need to work late/ on weekends. On the other hand, in academia, bioinformatics researchers tend to work in a more relaxed environment. There isn’t such a focus on harsh deadlines although there is still pressure to publish and secure funding. While this is a general trend, it can depend on the job role. For instance, there are industry roles that are more relaxed, and academia roles that are more fast-paced.
Funding and Collaborations
The second comparison we will look into is funding, and collaborations. Before we delve into this though, I want to explain how academia and industry fundamentally have different goals. In academia, the focus is on advancing the field by creating new knowledge and understanding, without an immediate practical application. Whereas in industry, the goal is for a company is to make money/ a return on investment. This is why we see a difference in not only the funding sources in academia and industry but also the resources that this funding is put into. Resources and funding in academia are often provided by government agencies or non-profit organizations, whereas industry is primarily funded by the company itself or investors. There is generally less money in academia for resources, and getting funding is harder. Researchers will have to apply for grants to be able to fund their work, and there is an ongoing requirement to apply for funding. In industry, there is a constant stream of money coming directly from the companies' profits. A company will happily reinvest its money if it can lead to more growth.
In terms of collaboration, academic bioinformatics often involves collaboration between researchers from different institutions, as well as between researchers and clinicians, to advance the field and develop new solutions to important biological questions. Industry bioinformatics typically involves collaboration between bioinformatics professionals and other experts, such as scientists, engineers, and clinicians, to develop new products and services for the market. Both academia and industry benefit from collaboration and cross-disciplinary partnerships, as they can bring together diverse perspectives and expertise to tackle complex bioinformatics problems.
We will now look into how the career paths compare in academia and industry.
In industry, bioinformatics professionals can have a clear path for career advancement and growth. You may start as a junior bioinformatics scientist and work your way up the ranks as seen in the image above. Eventually you can reach a management position or stay as a Sr Bioinformatics Scientist if management is not for you. There is also the option to move laterally in industry, for example into a more engineering -focused role, as companies will often have engineering teams working alongside bioinformatics teams.
In academia, there is also a hierarchy to climb. If you join a lab after completing your undergraduate degree you can become a research assistant/associate. You can also join a lab to do your PhD. After completing a PhD, you can become a postdoctoral researcher/ postdoctoral research associate and then you can move onto a professor track, working your way up to becoming a full professor.
A common question I get asked is 'do I need a PhD?'. In academia, if you want to climb to those higher positions, then a PhD is required. In industry a PhD is not required however it can help you move up the career ladder faster and be more competitive for promotions. Ultimately, the decision of whether to pursue a PhD or not should be based on your own interests, career goals, and financial situation. While a PhD can open up many doors, it is a significant commitment of time and resources, and may not be the right path for everyone.
Pay and Compensation
The final point we will cover in this article is pay and compensation. Pay is one of those things that can be very subjective. It depends on the organization, location, exact job role etc. But generally, Industry has significantly higher pay. To showcase this, I have collected some data from Glassdoor comparing the average postdoc salary with the average bioinformatics scientist salary across the US. See the figure below.
We can see that on average, the postdoc can expect to earn ~$75K whilst the bioinformatics scientist can expect to earn ~$116k. That’s a 55% increase. In terms of other compensation, it really depends on the organization. In my personal experience I had similar paid time off in both academia and industry but in industry I have a pension match and yearly bonus which I didn’t have in academia. But again, this is very subjective and not necessarily a general trend.
To finish off I will concisely summarize my personal experience working in academia vs industry. Industry pays more and has better compensation but is more stressful. Academia was more relaxed and had a better work-life balance but at the expense of less pay. For me personally, living in a HCOL area on a low salary did impact my quality of life which is why moving to industry was the right decision for me. The decision to choose between academia and industry ultimately depends on individual priorities and circumstances, and both options have their own benefits and challenges.