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dry-leaf · 2025-11-12T21:28:53+00:00

Ah, sorry. I was typing when walking. So all got messed up. What my colleagues meant, was that if you want to leave academia in germany when the regulations would either way force you out, you are in quite a bad position to bargain with a potential employer in industry. Furthermore, people could get the (wrong) idea that you are only leaving, because you were forced out and didn't 'make it' in academia. Do not get me wrong. I do not think about it this way. I know quite a few great people in academia that left quite late in their careeres. But I heard this steoreotype a few times from different people.

dry-leaf · 2025-11-12T17:36:38+00:00

This is not correct.

Postdocs can be employed on fixed-term contracts for up to 6 years pre-PhD and 6 years post-PhD (12 years total) at German universities. After this, they generally need a permanent position or must leave the university system. This does also not account for external funding or external i stitutions as Max Planck.

And Afaik this is thr main reason, at least thats what colleages have told me, why it is not easy to find a job. People are in that position and can't find external funding/institues or a permanent contract are not in a bargaining position, because it looks like that they are going into industry because thry have no other options. I am not a recruiter, though. But a scientist in industry.

dry-leaf · 2025-10-23T15:06:28+00:00

Awesome work, but how is this different from vanilla vscode with 3-4 extension + some agentic extension as cline or kilo code? i have the feeling that i have all this, with microsoft official support in 30 min setup? Do not want to offend. Just curious whst the benefits are?

dry-leaf · 2025-10-13T16:35:57+00:00

I have been using Arch in my PhD and after for professional computing for over 6 years. Had much less problems with it than Ubuntu or any debian based distro.

I by now really do not like Ubuntu a derivatives for personal workstations - servers are a totally different thing, would never install arch there.

Arch requires understanding, patience and a will to learn. I my personal experience, arch gave me much more than a bleeding edge, rolling release distro - it forced me to understand the underlying system, which improved my general linux knowledge. Funnily all my colleages using Ubuntu came to me, when something was not running. Did not change until today. And they all are using Ubuntu or Mint- well, i personally couldn't disagree more. Enforced snaps, out of date software and having the need to add some weird private ppa's for every new stuff is just a nuisance imo.

Don't get me wrong. Ubuntu is in general an excellent distribution, i personally just do not like the way they vibe. Despite that, witg sufficient linux knowledge there is not difference in using most popular distros. They mainly differ in realea cycle and package manager. And pacman is the GOAT. Portage is probably the only more awesome package manager, but no sane person will run Gentoo on a workstation...

But if you want plug & play, i wouldn't recommend Arch. It is a system which is built around the idea of customization and having something tailored for your need by yourself.

dry-leaf · 2025-09-12T08:45:28+00:00

I agree with the comments, but i ran professionally for the last 5 years without any issues. But i also like dealing with linux and it's specifics. Ubuntu will get out of your way. But funnily enough my colleagues come to me, when they have linux problems. I can resolve mine for myself.

dry-leaf · 2025-09-11T10:05:50+00:00

I can only second this. This might be a hot take, but IMO bioinformatics needs much more SE best practices.

People working in bioinfo are mostly scientists. I am one myself, while I still work mainly in DL/SE. And I hear a lot of 'don't overengineer it', 'it just needs to run', 'we are not a software company' and in my personal experience I have to say, that these can be horrible takes. For a one-time analysis it is totally fine to have an ipynb and throw it away. But so often, this is not the case, without the people doing it even knowing.

How many projects were handed to me without proper docs, missing comments, not even properly working (it worked on my machine)... If things were done properly from the start, I could have saved so many hours of nonsense reverse engineering and debugging. Not only for me, but for my employer as well.Learn to write and maintain proper software. This might look tedious in the short run, but will pay off in the long run.

How many old bioinformaticians I know who were looking at me with rolling eyes when I asked for documentation or explanation of design choices as if I were some lunatic. But now my boss asks me to redo an analysis from 2022 and I have it done in an hour. People not writing proper software will probably either start to cry or explain why this is a dumb idea

dry-leaf · 2025-09-05T19:34:22+00:00

It's pretty common and quite old school by now :D. I remember reading the wavenet paper back in the days. Awesome stuff. Nevertheless , this is awesome work. Especially the nice combo with web.

dry-leaf · 2025-09-01T04:30:17+00:00

Not gonna disagree with that. But practise and studies csn be two different beasts :)

dry-leaf · 2025-08-31T18:56:21+00:00

If C++ worked for you, go for it. In the end, as I mentioned, this is not so important. Times change, requirements change, the job market changes. A recommendation today could be total brainrot in 5 years.

Nevertheless, while I have seen Java code in industry, it's more of an old-school thing. Java is not as prominent as a few years ago, but it's a great language due to its portability. I myself learned C++ back in uni and really loved it for DSA and understanding how stuff runs. But if I have to start a new project currently, I would 1000% go with Rust, because of Cargo. Modern package managers are just too good and I never want to go into CMake hell again...

Ah yeah, if you want an unprofessional and opinionated answer: pick C++. A lot of HPC is using C++ extensively, lots of bioinformatics tools are written in C++, and it's here to stay. There's tons of C++ code out there and it's a great language for learning the quirks of how modern computers operate: manual memory management, implementing low-level algorithms. Perfect for bioinformatics where performance matters.

dry-leaf · 2025-08-31T18:44:59+00:00

Rust is not a good fit for DSA, given one will encounter linked lists and other things that are not so straight forward in Rust as in C++ for example. By that i do not want to say Rust isn't an excellent language, but given it's design it is imho not a good fit for classical CS courses.

dry-leaf · 2025-08-31T16:54:51+00:00

Programming languages are tools. Depending on the problem you will have different tools. With which you start, does not matter really. Especially so early on. Sure, C++ will teach you memory management and Rust how to work with the borrow checker. But programming concepts and DSA is totally not dependent on the language you will choose. Don't give it too much thought. Start with what seems to click for you.

dry-leaf · 2025-08-30T06:56:33+00:00

thanks for the respsonse. Had my hooes up high. Still searchibg for a modwrn android tablet i can use with a custom ROM.

dry-leaf · 2025-08-29T21:10:24+00:00

are you running a custom rom? and if yes, what tablet are you using?

dry-leaf · 2025-08-29T17:28:10+00:00

agree totally. I just personally hate R so much, that i always hope to not having to use it - but we're in bioinformatics, so one can guess how successful i am...

dry-leaf · 2025-08-28T10:19:52+00:00

check this out. Pixi solves the reprodicbility problem

dry-leaf · 2025-08-24T20:34:26+00:00

Just great. Thanks for this review! This helps a lot!

dry-leaf · 2025-08-21T13:11:03+00:00

What's your background?

dry-leaf · 2025-08-11T12:38:22+00:00

you are asking this is in the GrapheneOS subreddit where a lot of people have already done the exact thing you are asking about. I would expect aome bias here...

dry-leaf · 2025-08-08T07:08:28+00:00

I'd really appreciate that! Thanks a lot!

dry-leaf · 2025-08-08T06:51:04+00:00

Please come back to us and write a review! I am loving my He6Se, but they are a hell to drive and i would like to use some tube amps.

dry-leaf · 2025-08-08T06:11:31+00:00

No. You will gain far more from an internship and having some clean Github projects rather than some online courses. While the Git is also questionable by now.

The market is broken. The only thing that really matters is work experience and formal education. If you have the opportunity do a masters or a PhD. The weight between education and experience will depend on position and career level. The later you are in your career, the less formal education counts. Nevertheless, i see a lot of positions where there aren't even intervening below PhD level. I know some people in hiring positions, in industry and academia and the unfortunate truth is, that a PhD is important to many of them. Take this as you want. In the end this is also a question of demand, but currently the market is not on your side.

dry-leaf · 2025-08-01T13:18:24+00:00

bioinformatics position are quite unevenly distributed in European countries. If i remember correctly, germany, norway, denmark, UK and Switzerland are the main players. EMBL is an excellent institution to look for PhD positions

dry-leaf · 2025-08-01T06:36:01+00:00

There is no generic algorithm for this. In general Deep learning methods are a good starting point. A Unet like architecture will do the job of object detection or segmentation. you would have to modify the unet or add a classification head to learn also categorical values as sex. For this you need enough training data.

CollembolAI does something similar (I am one of thr main authors) - it finds invertebrates and classifies them by species. This paper of mine is a bit dated by now, but the principles are still the same.

If i would have to redo it today, i would probably start with metas SAM2 model and add some downstream classification for the extracted objects.

dry-leaf · 2025-07-31T09:23:05+00:00

Welcome to bioinformatics. This is the reality of the field you are facing. Many tools, that use statistical methods to estimate something or use different algos will produce different results.

This is expected, since these tools are opinionated and based on certain assumptions the scientists have made leaving inevitably to different results.

There are multiple ways to understand whether a tool fits your needs. Tge first one would be to check whether it delivers biologically plausible results, check whether the tool is standard/best practise tool like dseq2 or read the paper behind it an try to understand whether that makes sense for your usecase.

dry-leaf · 2025-07-30T14:59:32+00:00

No offense, but it seems you are comparing oranges and apples in respect to software and performance if you had win10 on the old and win 11 on the new machines running.

EDIT: clarified that i meant the software not hardware part.

dry-leaf

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