Thrilled to share that our company @LilaSciences is emerging from stealth mode🚀! If you’re curious about harnessing LLMs for groundbreaking scientific discoveries, join our happy hour🍸 next week in Vancouver at #NeurIPS2024. Registration is now open! 👇👇

Can science create the next scaling paradigm for AI? We think so, and we'll be using our recent Series A raise to build a new kind of scientific reasoning model at scale. If you're interested in how we think all of science is subject to the bitter lesson, read on in the 🧵👇

A big day for @LilaSciences , where I’m leading open-endedness. A frontier lab focused exclusively on advancing the singularly open-ended enterprise of science can make bold and unique bets that are off the radar of the chatbot giants. It’s a great place to work and do research!

🚀 Big milestone: We raised a $235M Series A, co-led by Braidwell and Collective Global! Our team is excited for this next chapter in building the world’s first scientific superintelligence platform to accelerate breakthroughs in life, chemical, and materials sciences. 📣 If the

So excited that we get to work with @kenneth0stanley on open-endedness for scientific AI @LilaSciences! Ken is truly one of the most original thinkers I've ever met in addition to being an amazing colleague. PS - His open-endedness team is hiring, come join us! Job links 👇

We are excited to share an initial look at what we're building at Lila Sciences! At Lila, we are weaving together several exciting threads that have emerged in AI over the last several years: Highly-capable large language models, generative models of biomolecules and materials,

🍹🍸@LilaSciences

I have 3 open postdoc positions in my group. Machine learning and AI to topics varying from inverse molecular design, optimization of near-term quantum computer algorithms to multi-scale simulations of electron transport. All project are exciting collabs. see thread for links:

🩴🩴FLIP is excellent work on exploring local (e.g. GB1) and global (multiple protein families from Meltome Atlas) landscapes. For FLOP, our focus shifted to the intermediate landscape, pertaining to a specific protein family with diverse wild types and ML- generated sequences.

Train a diffusion model on coarse-grained samples, and in addition to generating CG samples, you also get the CG force field! @artsmarloes @vgsatorras @chinwei_h @danielzuegner @mfederici_ @cecclementi @FrankNoeBerlin @rpinsler @vdbergrianne https://t.co/6a9ZV0RRnA

Results for this competition are online since a few days. Interesting that the very good intermediate results (Rs=0.8+) were mainly due to people overfitting to the public test data 🥸. Final winner achieved Rs ~0.55 for the private test data. 1/2

Do you like machine learning, proteins and Copenhagen? Check out our open PhD position: https://t.co/THKBz3IoBD. Deadline Jan 22. Please RT.

Exploring the vastitude of sequence space..happy to share just published work with @rob_best_ @pengfei10 on boosting protein thermal resilience through an interplay of co-evolution driven sequence generation, MD simulations and experiments!

PhD fellowship in structural bioinformatics available in the group in our #PRISM centre 🇩🇰 If you love proteins, know a bit of programming and like to do quantitative analyses based on protein structure and sequence, this might be for you. https://t.co/MQqFbvm69j

And the structure of the protein (wild type) in the test set 👇

Please help to spread the words ❤️ @LindorffLarsen @KevinKaichuang @sokrypton @smnlssn @_amelie_rocks @ElePapaleo

Only 10 days into the competition, more than 400 teams have joined the competition. It is exciting to see both machine learning and physics based methods have achieved impressive performance. Hope more and more people will join this competition in the next 3 months.

The benchmark of this competition is an internal dataset obtained from the high throughput screening lab 👩‍🔬🧑‍🔬 of Novozymes: experimental stability of ~2400 protein variants of single-point mutation. The winners will share the prize of ~25,000$.

Novozymes A/S invites data scientists and protein scientists around the world to look into this scientific challenge: predict protein thermal stability. The competition has just been launched on the Kaggle platform 🔥. Link:

...if you are looking for a staff scientist in computational biophysics to join your lab: then write to me in private.