Traps you’ll fall into, when mixing different things

Doing research in industry as an industrial researcher is fine. Doing research in academia as an academic researcher is fine. The problems start when you mix the two, especially for young researchers. Like industrial PhD students. Like me.

Having one foot in academia and the other in industry has its pros and cons, as everything in life. Being guided by two very different kinds of supervisors, with different attitude and motivations, is definitely a stressful con. People in industry have a “make it work” attitude. If you are developing something, it must work, and it must be worth money. If something is not worth selling, just stop caring about it. People in academia can go deeper. They must understand why something isn’t working. And none of them is right or wrong. They simply have different jobs. One sells products that need to be made fast. The other sells results of deep and long investigations.

A small personal experience on the two different approaches: I was stressing because a model I was developing was not working well. My industrial supervisors helped me a lot, but their attitude was always the “let’s make it work, so we can use it” attitude. Here it is the “result-oriented mindset” we see so much in job posts (and often in our CVs): I am developing the model so that in the future, my company could press a button and predict when their parts will fail. I fell into the trap of believing this was the standard procedure: I had to make the model work, otherwise my job would be unsolved, and no PhD for me! But in academia that is very far from the standard procedure. When I showed my worries to one of my academic mentors, he said “In the last 40 years, researchers have tried to develop models for materials much simpler than yours. Do you really think you can develop an absolutely accurate model in 3 years and put an end to this research field?”.

Like it was for me, if you are working everyday in a company, you might start to forget that you are still an academic researcher. And you might make the mistake of comparing yourself to your everyday life colleagues. Sure, things might not work for both you and them. But in their case, when facing with non-promising results, they are often re-directed to other topics. This is not an option for PhD students in industry. You have your research, and you have to develop it for 3-4 years, for better or worse.

Therefore, dear stressed (industrial) PhD student, don’t try desperately to develop amazing technologies all by yourself. Don’t compare yourself to your colleagues in the company, who have much flexibility of work. Don’t compare yourself to your fellow PhD students in university, who can also benefit from more guidance. But most importantly, do not fall into the trap of the “it has to work” attitude. In academia if something works perfectly, it’s often not even worth investigating. It’s ready to be sold by companies. Even if you are in a company, you are still an academic researcher, and your job is to investigate things that don’t work. Finally, remember that your objective is not to make your company rich, but to get your degree. If you develop something that for a company is not immediately usable, it’s still ok. Not working technologies (like my previous inaccurate models) are necessary steps into working technologies, and are thus worth academic publications, which is all you need. Finding a balance between the needs of your industrial and academic supervisors is a key.

In this sense, an excellent skill to develop is learning to say no. But that’s a topic for another post…


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