1. From “scientist” to software developer

If you are a scientist wanting to do real science and make money out of that, this post is for you.

8 years ago, I choose to become a software developer after finishing two degrees in mathematics & physics and I hope you will do the same.

Why do we need more scientists?

We can ask the question to the first computer scientist that builds the first digital computer:

“We shall need a great number of mathematicians of ability” because “there will probably be a great deal of work of this kind to be done”

— Alan Turing [http://www.turingarchive.org/viewer/?id=149&title=18]

During a talk Robert C. Martin told us that each 5 years, the demand for software developers in the world doubles. There is no field in science (and probably in general) benefiting of such a growth.

The demand soaring and the offer is scarce.

Software is the best way to do science, period

This is how the creator of C++, Bjarne Stroustrup, put it:

One of the things I really like about programming languages, about IT, is it is a perfect excuse for sticking your nose into interesting projects in just about any field. And so, if you’re interested in high energy physics, in the structure of the universe, being a programmer is one of the best ways of getting there; it’s probably easier than becoming a theoretical physicist

— Bjarne Stroustrup [https://www.youtube.com/watch?v=86xWVb4XIyE]

And, trust me, he’s right, I tried to become a theoretical physicist and it’s hard.

I will go further than Stroustrup here: I think becoming a software developer is the best way to become a great scientist. Most of the economic boom in tech of the last 3 decades can be explained by this:

the short feedback loop of a software experiment

We know science evolve with the falsification principle. And the faster you do your experiments, the faster you know if your hypothesis is wrong. And the more we digitalize our experiments (by simulation on computers) the faster our Science evolves. Computers don’t wait a Phase 3 clinic test, it doesn’t wait you to build an airplane wing to tell you if it’s optimal in terms of airflow, it doesn’t wait for your new laboratory to be constructed to answer you. If you can enter the fundamental laws of your experiments in the computer, it will answer you immediately. The more you are versed in computer science, the more you will be able to digitalize parts of your experiments and accelerate your thinking.

Conclusion

If you are a scientist, I hope you will find a way to leverage this in your career or your current work. If you are interested in unleashing this ubiquitous computing power around you, here are some resources to get start:

• Learn programming languages like Python, Swift or Java
• Learn to digitalize your ideas by writing algorithms Introduction to Algorithms

Or if you’re still interested, read on the first step on the software development journey…