Clinical haematologist / cancer researcher here. I work mainly 80% clinical work and try to fit in research into the rest of the week and evenings. My PhD worked on bigger data than could be analysed in the regular biological sciences way (excel + stats software), so I learnt R. That led me down a rabbit hole of learning linux, bash, bit of Go, python etc.. I can't remember how I ended up here. I think maybe the instructor for the Go course mentioned it. I stayed because I find the science-based articles interesting and I like to draw comparisons across different disciplines.
The quality of the discourse is high here, so I'll stay as long as that's the case!
Hey, that’s awesome! I’ve been working as a software engineer in various companies for years now doing mostly Go development these days. I’m very interested in switching my career to cancer research and doing a PhD, potentially on immunotherapy. May I ask what you’re using Go for? Also, I’d be curious to learn more about your research work.
Oh sure - biomedical research is in real need of a combination of programmers / statisticians / bioinformaticians and regular scientists at the moment. The latest research techniques are terrific at maximising the amount of information extracted from precious samples. While definitely a good thing overall, it introduces new problems, like multiple testing and simply crunching lots of data.
My PhD was in cancer-immunology. I was looking at the interaction between the immune system and lymphoma cancer cells. It was a particularly interesting area because the cancer cell and the reactive immune response were, once upon a time, the same cell. We used several high dimensional techniques to identify cells, including single cell sequencing, which can measure the production of up to 20'000 genes per cell on several thousand cells. I also used something call mass cytometry which binds around 40 antibodies to individual cells looking at what's on their surface. It was great stuff and I'm still working on some of my data from it (analysing it is still a bit of an unsolved problem!).
I learnt Go because I realised that I was using R without understanding programming. I loved using Go, it's a great imperative language, but maybe not that suited to run-once analyses of numbers (I know writing this someone will prove me wrong!). I did a bit of mathematical modelling in Julia too, and really enjoyed that. I'm actually a big fan of R - once I got my head round using it in a functional style, it's very elegant for my work.
If you wan to do a PhD in cancer research, probably worth contacting Professors to see if they're aware of any interesting projects and talking to the people supervising them. My advice is to do something you're genuinely interested in and have an adviser that you will be able to get along with even in times of acute stress! Good luck!
Thanks for the details! Sounds like you’re doing the kind of things I’d love to do for the rest of my career. Indeed I’ll have to start reaching out to people to figure out where I can do what interests me. I’ve been hanging around the r-bioinformatics Slack for a while now (not sure if you know it) and it’s impressive to see how much this field took off. I have limited experience with R (and Python), but it’s a great language to master. I haven’t played with Julia yet.
The quality of the discourse is high here, so I'll stay as long as that's the case!