211–220 of 299 posts
Related HN discussion (May 2022) on similar article: https://news.ycombinator.com/item?id=31577376 https://www.nature.com/articles/d41586-022-01516-2 > "Fundamentally, RSEs build software to support scientific research. They generally don’t have research questions of their own — they develop the computer tools to help other people to do cool things."
I’ve had a growing interest in the power of DNA and what the data can be used for since discovering no less than 3 family secrets (one of which pertaining to me) after taking an Ancestry DNA test. Did I know I was going to find 18 half siblings the moment my results came in? Nope, but yet there they are, listed in order of most shared DNA. Despite my interest, I’ve found that landing a job in this field at my desired…
Yeah the low pay is one thing, but in my experience a lot of the academic jobs seem to want a domain scientist who can do programming, not the other way around.
> the biologists first come up with the first concept of the tool, which is purely focused on ensuring good results. After this first iteration is completed, engineers then come in and rewrite the tool using modern engineering practices with things like speed and reliability in mind. I think that is already accepted as good practice, and the way most people in the field work, which is part of the reason why the field…
Accounting is a bit different, because it has already been invented. There are standards and best practices for it. In bioinformatics, writing software is often a research activity. You write software to determine what the software should do, and then you adjust your ideas and rewrite it. The person writing the first version(s) of the software is a researcher – at least in practice if not by job title.
I am a career SW engineer that has worked on genomics in a startup. The field is genuinely exciting. The endemic disease of the field is the leadership. A leadership made out of Principal Investigators forged in academia, appear simply incapable of producing any item which is not articles (or equivalents thereof).
Call me when non-tech fields learn to treat engineers as equal partners rather than disposable labor. Academia? Yeah they're going to be one of the last to realize, PIs don't want to cede any power in their little fiefdom. Very familiar with the dynamics there.
Scope of PI interest / funding defined by research grant. So, unless research is ground breaking / exploritory across disciplines, supporting disciplines tend to be extremely limited by PI research interest. aka (wording sanitized a bit) tends to come across as being tight wad / ham fisted
Treating a position with limited available applicants as if there were to many available applicants is always a receipt for issues.
20 years ago I got interested in "bioinformatics." I loved learning something about molecular biology, after all those years of hearing about DNA and not understanding it. And "Molecular Biology of the Cell" is, hands down, the greatest textbook ever written. That said: a lot of the comments are spot on. You're working in a field where the hard scientists and business people rule and you're a helper. Maybe they're gr…
I have worked in a genomics lab after finishing a bioinformatics master's. It was my first fulltime job, and by far the most chill. People were great. The PI was laid back, the whole lab went out for beers every now and then - and not because of a mandatory startup-style 'bonding' event. We genuinely enjoyed each others company and hung out outside of work. I never had that in any other job, which were/are all commer…
20 years ago I got interested in "bioinformatics." I loved learning something about molecular biology, after all those years of hearing about DNA and not understanding it. And "Molecular Biology of the Cell" is, hands down, the greatest textbook ever written. That said: a lot of the comments are spot on. You're working in a field where the hard scientists and business people rule and you're a helper. Maybe they're gr…
Molecular Biology of the Cell got me extremely excited about genetics and bioinformatics, highly, highly recommend this book to any software person I meet who is interested in biology. As to the work environment, it seems to be extremely varied depending on the lab and team your on. I came from a number of years doing web development in marketing and finance before joining an R1 university research lab, and in many w…
Our company values software quality and we're very product focussed. We're actively hiring in London: https://news.ycombinator.com/item?id=33423547
The author completely neglects the downsides: - The compensation absolutely do not match the workload and education required. - The sheer number of disreputable PIs and their unrealistic goals for software. - The data is likely questionable and often underpowered. - Institutional politics. everywhere. - Marketing ("Curing Cancer"). The role is actually just juggling various bioinformatics file formats.
> just juggling various bioinformatics file formats Your other points are spot on. This one I want to address specifically. The file formats. Academics love their incredibly over-engineered file formats. MARC. SGML. DICOM. HL7. RDF. Those are just the ones I know. Universally, they try to cover every corner case that anyone could ever imagine. Academics absolutely love their ontologies. Just implementing one of them…
The downside is it's a giant hellscape of unstructured, poorly specified formats where data types are barely specified at all or if they are most of the schema is published on some rambling blog post by some rando scientist. You will spend most of your time understanding it by empirical reverse engineering of the data that you are trying to deal with.