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submitted 3 days ago by fossilesque@mander.xyz to c/science_memes@mander.xyz

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[-] thevoidzero@lemmy.world 26 points 3 days ago

Honest opinion programming is easy and fun when you learn it and it saves you time and allows you to test your ideas. Creating something gives you dopamine.

Problem is before people even try any programming for themselves, they are introduced to it through school or work where they have to do it for homeworks or analysis while also learning new things. And they hate it.

[-] atomicbocks@sh.itjust.works 12 points 3 days ago

I didn’t really start hating it until not doing it for 13 hours a day meant losing my job because, and I quote, “we can have meetings all day because you have all night to finish your work”.

[-] blackbirdbiryani@lemmy.world 12 points 2 days ago

Maybe a lukewarm take now, but you can no longer expect to succeed well in biology if you don't have at least an intermediate understanding of programming and statistics.

Without the former, you are going to be wasting a lot of time doing manual work (I kid you not but I see my co-workers waste literal hours gazing at matrices in Excel like they're gonna land on a significant gene by accident).

Without the latter, you are going to be wasting thousands of dollars in reagents and working time running experiments that never had the hope of succeeding (what do you mean I need more than one replicate?).

Yes you can stick to lab work but don't expect to get paid more than the average janitor, because you're competing against literal thousands of graduates who can use a pipette but not R. Maybe if you were a specialist in an expensive niche equipment like flow cytometry or mass spectrometry, but surprise surprise, these kind of equipment require an even more advance understanding of statistics to understand/process the results.

If you're a biologist who thinks you hate math, I promise you programming is more approachable than high school math, there's so many tutorials available these days for free that are leagues better than any material from your professor.

Try to get as many opportunities that involve command line work on clusters, analyses with R, and maybe python as well, and you'd be a candidate that would stick above the rest. Programming and statistics is rapidly becoming a common competency, and if you don't have those skills you won't be able to compete with people who do.

[-] someacnt@sh.itjust.works -4 points 2 days ago

Is programming skills that important in days of LLM where companies are replacing juniors with AI?

[-] baguettefish@discuss.tchncs.de 3 points 2 days ago

absolutely

[-] barsoap@lemm.ee 1 points 2 days ago

It would've been smarter of those companies to replace the bosses with AI.

[-] Venus_Ziegenfalle@feddit.org 16 points 3 days ago

Vivisection too

[-] Lembot_0003@lemmy.zip 10 points 3 days ago

What does programming have to do with animals?

[-] PM_ME_VINTAGE_30S@lemmy.sdf.org 31 points 3 days ago

Humans are animals, and humans invented programming. Therefore, programming is applied biology.

[-] Lembot_0003@lemmy.zip 19 points 3 days ago* (last edited 3 days ago)

Descart: What an excellent time to be long dead and therefore not need to even think about this logical abomination of a sentence!

[-] jol@discuss.tchncs.de 16 points 3 days ago

Science researchers and students often spend a lot of their time doing statistical analysis, including using programming for that.

[-] Peanutbjelly@sopuli.xyz 5 points 3 days ago

Bayesian analysis of complex intelligent systems via friston's free energy principle and active inference? Or machine learning?

Personally love the stuff circling Michael Levin at tufts university. I could also imagine there's a lot of unique model building in different biological/ecological niches.

[-] Midnitte@beehaw.org 3 points 3 days ago

lm(turtle_gender ~ temp, data = data_frame)

[-] friendly_ghost@beehaw.org 2 points 2 days ago

The turtles are not safe from Python

[-] propter_hog@hexbear.net 3 points 3 days ago

Computational biology and ecology are a huge part of those fields. I work at a research lab (in computer science) and one of our sister labs is dedicated to environmental stuff and has mostly biologists and ecologists employed at it; a large part of the research they do involves supercomputing somehow, so we tend to partner with them a lot. As an example, modeling population growth or decline due to a change in the population's environment is one such use of computing and statistics in biology and ecology.

[-] rustydrd@sh.itjust.works 2 points 2 days ago

Probably Python and R for statistical analysis, which is common nowadays in most empirical sciences.

[-] Zenith@lemm.ee 3 points 2 days ago* (last edited 2 days ago)

This is why I stopped pursuing my degree, I’m never going to work in a lab stop trying to force irrelevant knowledge on me, granted it was psych not biology/ecology