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The difference in scientific research in academia vs industry

This piece discusses why researchers might want to transition from academia to industry and how scientific research in industry differs from scientific research in academia.

By Aimee Cichocki in Guides

Almost all research scientists start their careers in academia and reach a turning point where they decide whether to stay in academia or move into industry.

This piece discusses why researchers might want to transition from academia to industry and how scientific research in industry differs from scientific research in academia.

Why would you want to transition from academia to industry?

Several key differences in the two environments should be considered before making the leap from academia to industry.

Salary

Scientists working in industry tend to earn more money than those in academia. The BioSpace 2020 U.S. Life Sciences Salary Report found that the average salary for life science professionals in academia was $82,516 for men and $58,966 for women. Salaries are far higher in industry – on average, $144,181 and $129,480, respectively.

BioSpace 2020 U.S. Life Sciences Salary Report

Source: BioSpace 2020 U.S. Life Sciences Salary Report

Funding

In academia, you’re often required to secure your own funding, and most of your time might be spent writing grant proposals and lobbying for funds. In industry, the funding aspect is typically taken care of by someone else at the company.

Measurements of Success

In academia, success is usually based on the number of publications and citations from your work. In industry, success is often measured by the impact of your research on the bottom line, for example, by meeting product release deadlines and sales goals.

Impact

Many scientists who transition from academia to industry find that their work has a more meaningful immediate impact. Research in academia aims to expand the field of knowledge on a specific topic to add greater understanding to a field. But this can mean that the research may lack practical and immediate significance. Research in industry aims to develop a product or service that will have a measurable impact on a company’s bottom line. These developments are often accompanied by a well-defined vision and product release plan. Researchers in industry also need to think about ideas from a business perspective. For example, just because a drug is efficacious doesn’t mean it is a viable product (key considerations might include market size, competition, manufacturing complexity, and production costs).

Autonomy

Scientists in academia usually enjoy autonomy in deciding which research topics they want to pursue. In industry, goals are tightly focused, so individual scientists often have far less freedom.

Pace

Industry research tends to have tighter timelines, particularly in a startup environment. Deadlines may be coupled with a highly-competitive environment, leading to stress and burnout. There’s also less room for error.

Outlook and Mindset

In academia, scientists are trained to take a dogmatic approach to research. While this has its benefits, it can become a hindrance in business, where startups often find success through flexibility and adaptability.

How do the required skills in industry and academia differ?

Because of differences in pace and autonomy, scientific teams in industry are more likely to invest in tools to improve research efficiency, such as collaboration. For example, they might use electronic lab notebooks (ELNs) instead of paper to record experimental protocols and research data and leverage laboratory management tools to make lab processes more efficient.

While modern tools and technology can improve efficiency and productivity, they often involve a steep learning curve and can be overwhelming for researchers who are used to a traditional approach. For example, scientists entering industry often need to learn a whole new set of skills to collaborate with their colleagues, communicate effectively, and allocate their time and resources.

How to obtain the skills required to transition into industry

One of the key things researchers transitioning from academia to industry should learn is project management. Many scientists pursue a Project Management Professional (PMP) certification, an internationally-recognized certification offered by the Project Management Institute (PMI).

While you might have been exposed to project management within academia, a role in industry requires that you hone many specific skills under the project management umbrella, including communication, collaboration, time management, and resource allocation.

Communication

One of the main hurdles when entering the business world is that, contrary to academia, not everyone will speak the same scientific language as you. In industry, often, you’ll have to explain your work to management teams or external parties who might have little to no scientific background. It’s also possible that you’ll be working with technicians, with whom you’ll need to communicate a very specific process and who will likely have less context than you.

It’s vital that you learn effective verbal and written communication, which may mean relearning what you have been taught in academia. In industry, academia's formal, technical communication style is replaced with concise, direct language. Many interactions will revolve around politics, money, and relationships, not just the science itself.

Much of this can be learned with experience. Still, there are specialized courses you can take to hone your communication skills; for example, those offered by the American Society for Biochemistry and Molecular Biology and the Canadian Center for Science Communication.

Collaboration

In academia, research is typically siloed such that there is minimal collaboration. The opposite is true in industry. It’s often necessary to forge relationships with researchers and other stakeholders who offer different perspectives and have different roles, priorities, and deadlines.

It could be beneficial to participate in a course such as the Nature masterclass, Effective Collaboration in Research, to enhance collaboration efforts. This particular program draws from the expertise of both academics and professionals, so it could be especially helpful for researchers looking to bridge that gap.

Resource allocation

While you don’t have to study in-depth accounting, any scientist looking to forge a career in industry should have a solid handle on managing expenses. With limited time and resources, you need to be able to determine where they are best spent.

Many courses of varying technicality are available on this topic, but one particularly useful resource is the book Cost Analysis for Engineers and Scientists.

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