PhD and working in the industry

Working in the industry provides an excellent opportunity to apply your hard-earned research and technical skills in practice towards developing products/services of value. You get to work in a relatively polished and systematic work environment where the nature of work changes as the competitive business landscape changes. You get to work with top talent in your field in a diverse work culture spanning geographical areas (and even continents) towards a common goal of delivering a high-value product/service to your customers/clients. Due to the length and breadth of technologies involved, there is reasonable freedom to choose a role you enjoy and are good at. As you develop more skills in your work, you earn more autonomy.

Any role in the industry would involve a combination of the following.

1. Product development
   Depending on your industry and role, it will involve one or multiple of the following: running experiments, data analysis, software/hardware development, testing, validation, process engineering. This would take the bulk of your time and essentially justifies your addition to your company’s headcount.
2. Background research / skill development
   Understand the state-of-the-art, hot topics, pressing problems, limitations of the state-of-the-art, verifying, and validating your methodology and approach with the literature. Develop new technical skills for your current/new role as needed.
3. Developing intellectual property
   Develop methods/algorithms/techniques to solve a pressing technical problem. Occasionally file patent applications on some of those.
4. Publications and conferences
   Writing white papers, research papers, and participate in industry/research conferences in your field.
5. Contribute to the standards bodies (such as IEEE, ISO, ITU, etc.)
   Influence the technical direction of your discipline and represent your company.

In the early years of your career, you are expected to spend a significant % of time on (1) and (2) and get your feet into the ground. As you mature and move up the corporate ladder, it will be spending more time doing (3) to (5), however, nothing stops you from doing it in the early years as well.

The bulk of the technical headcount in any company works on the product-development side of it. Some companies have a separate research division (aka research labs) with max. 5-10 % of the total headcount. However, those divisions are an increasingly smaller share of the company’s headcount (think IBM Research) [1] or have nearly vanished (think AT&T Bell Labs). Moreover, many new-age technology companies (like Google, Facebook) have almost done away with that structure [2].

Often, Ph.D. students are under the impression that they only belong to the company’s research side. However, that is increasingly less common, especially in the computer technology industry [2]. Between a role in the product-development side and the research side, the main difference is the % of time spent in the above five activities. Also, over the course of your career, you could be moving between product-development and research roles. Rather than obsessing over whether to work in the industry or a research lab, it’s better to focus on the specific skills you need to master to succeed in your career.

To succeed in the industry, we need to find the right fit for our skills and abilities. In our Ph.D. process, we spend a significant amount of time/energy developing certain skills relevant to a specific domain. As we start looking for jobs in the industry, we might realize that the domain and/or the skills are not as relevant for the market. So how do we go about finding the right fit? One exercise I find useful is to identify the knowledge domain and technical skills for a job opening. By domain, I mean the knowledge area of your research. By skills, I mean the specific tools/techniques/methods that you have mastered in your research area so far. Let’s consider an example. Suppose your research is in applying machine-learning techniques identifying tumors in medical images. Then your domain is medical imaging, and your skills are machine-learning (ML) techniques.

As you are looking at the job openings, identify the specific domain, and skillset it requires. Same way, identify the domain and skillset of your research experience. Ideally, going from one position to another (Ph.D. -> PostDoc or Ph.D. -> industry or PostDoc -> PostDoc), try to change either the domain or the skill. This helps in having a solid grounding in one while picking up the other. How about applying ML techniques to identify objects for self-driving cars or learn new statistical techniques (say deep learning) in the medical image domain.

References
[1] https://cacm.acm.org/magazines/2015/1/181626-the-rise-and-fall-of-industrial-research-labs/fulltext
[2] http://academicsfreedom.blogspot.com/2012/08/advice-for-phd-students-seeking.html