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patrickkidger.bsky.social
I do SciML + open source! πŸ§ͺ ML+proteins @ http://Cradle.bio πŸ“š Neural ODEs: http://arxiv.org/abs/2202.02435 πŸ€– JAX ecosystem: http://github.com/patrick-kidger πŸ§‘β€πŸ’» Prev. Google, Oxford πŸ“ ZΓΌrich, Switzerland
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We added Boltz-2 to our protein design package! Under the hood this relies on a JAX translation, which, thanks to @jeremywohlwend.bsky.social and @gcorso.bsky.social ’s clean code, was fairly easy to write. We’ve been getting great results -- and we have yet to explore the most exciting new features

πŸš€ Announcing: ✨`patdb`✨! A fast, pretty, TUI/REPL debugger for Python. (Not a database!πŸ˜„) Think stdlib pdb, but with... - Syntax highlighting - re-raised+grouped exceptions - robust to async/threading/multiprocessing - ... ! > pip install patdb GitHub: github.com/patrick-kidg... 1/3

πŸ”₯ Time for my first bioML blog post! This one is for all the folks getting into ML-for-protein-design. ✨ "Just know stuff, proteinML edition" kidger.site/thoughts/jus... This is intended as a curriculum-with-context, as a starting point for the field. 1/2

At CERN the next couple of days for a workshop. Send me a DM if you're around too πŸš€

Oh this is pretty cool πŸ˜ƒ ESM-C protein language model in JAX+Equinox!

πŸš€ I just spotted that we passed a really cool milestone: Equinox is now used by over 1k projects on GitHub. *And* we actually also just passed 1k commits as well.πŸŽ‰ (github.com/patrick-kidg...)

✨ We previously took 1st place on the Adaptyv protein binding competition. πŸš€ In this update, we now take all of *top 12*! Just one of our entries into the competion was tested at the time. Our prize for winning was to have our other designs be tested... Post: www.cradle.bio/blog/adaptyv2 [1/2]

🌟 We have a proteinML PhD internship at Cradle! jobs.ashbyhq.com/cradlebio/d8... Come see what it's like to work at a frontier bioML lab. This is a unique opportunity to work across the entire stack: πŸ”¬ Automated wet lab data; πŸ€– Train your own ~1B parameter ML models; πŸ“š Publish end result! πŸš€

🌟 We have a proteinML PhD internship at Cradle! jobs.ashbyhq.com/cradlebio/d8... Come see what it's like to work at a frontier bioML lab. This is a unique opportunity to work across the entire stack: πŸ”¬ Automated wet lab data; πŸ€– Train your own ~1B parameter ML models; πŸ“š Publish end result! πŸš€

πŸš€ It's time for a new JAX ecosystem library! This time quite a small one: ESM2quinox. A #JAX + Equinox implementation of the ESM2 protein language model. GitHub: github.com/patrick-kidg... SciML is obviously my whole jam. My open source has largely focused on the differential equations ... [1/2]

✨We're hiring for bio roles at Cradle! You can expect to work on a huge variety of problems (antibodies, enzymes, peptides, ...) across all modalities (therapeutics, agtech, biosynthesis, ...), as at this point (post series B) we work with pretty much the whole industry. [1/2]

✨ I wrote a new blog post! πŸ€– RealSemVer: or, how Semantic Versioning _really_ gets used. kidger.site/thoughts/rea...

In school, you probably learned that human cells have 46 chromosomes, which is 2 copies of 23 chromosomes, sometimes called 'diploid' or '2n'. But there are other 'ploidies' in your cells. To start with, 80+% of your cells have NO chromosomes: red blood cells or 'erythrocytes'...

FutureHouse is launching an independent postdoctoral fellowship program for exceptional researchers who want to apply our automated science tools to specific problems in biology and biochemistry, in collaboration with world-leading academic labs. 1/

πŸ”₯ How we won the Adaptyv Bio competition, designing a 1.21nM binder to EGFR using generative AI :) www.cradle.bio/blog/adaptyv... 🌟 This was a super fun project from four of us at Cradle Bio ! ✨

πŸŽ‰ Okay folks it's that time of year! Who's at NeurIPS?? Come find me and the rest of the Cradle Bio crew πŸ§ͺ Always happy to chat sciML, protein design, open source, and everything in between 🌟

✨ wheeeeee we raised a series B AI-powered automated protein optimization: matches or exceeds human performance, works without human intervention. It's pretty cool :D (PS if you're seriously good at ML eng then we're hiring) www.cradle.bio/blog/series-b

*Building neural networks in Equinox* Third lab for the course, after JAX and Keras we see Equinox (from @patrickkidger.bsky.social) - including callable pytrees, stateful modules, and filtering. Stay tuned for part b with a text classification model. 😎 colab.research.google.com/drive/19NHkb...