I was quite helpful to him and the other students (who mostly struggled with packaging: conda, pip, apt, etc). In turn, they were quite patient with my lack of biochemistry background. It was nice to get a taste without having to take what would've been 2.5 years worth of prerequisites.

1) The fellows writing papers - usually these guys have PhDs. Usually a science-focused PhD. 2) Analysts - often have a background in mathematics, biology, or big-data. Success here can lead to an onramp to camp 1. Much of your time here is spent in interactive programming environments, like Jupyter notebooks. 3) Programmers - writing novel or faster bioinformatic tools, often in low-level languages like C++ or Rust. Sometimes you can get a paper out of these, especially if you have a CS background. There's increasingly room for higher-level tools though here too, so it starts to overlap with 2. 4) Pipeline programmers - people gluing analysis workflows together out of the tools written in low-level languages, often with a liberal helping of Unix command-fu. Often sort of an ad-hoc role, containing people from diverse backgrounds, from biology to sysadmin. (This is my current role). 5) Biology/wetlab - people running experiments in the lab, and want to analyze their own work, especially for QC purposes. Wild-west ad-hoc development practices.

But bioinformatics is an umbrella term. There’re so many different things people do. I started by identifying field I’m interested in (ageing and immunology) and backtracked from there.