💫 As promised, we just released on GitHub the weights of the #FeNNixBio1 foundation machine learning model for drug design! 💫 Weights: github.com/FeNNol-tools/FeNN… FeNNol GPU code: github.com/FeNNol-tools/FeNN… The models are distributed under the open source ASL license (i. e. restricted to non-commercial academic research). You can also check the updated version of the preprint that includes a unified transformers architecture as well as the full computation of the Freesolv hydration free energies dataset etc... doi.org/10.26434/chemrxiv-20… Happy holidays and merry Christmas everyone! 🎅 🎄 Sorbonne Université / CNRS @qubit_pharma #machinelearning #moleculardynamics #drugdesign #compchem #GPU #biophysics

Thrilled to share our new work MatInvent, a general and efficient reinforcement learning workflow that optimizes diffusion models for goal-directed crystal generation. Thanks to @JeffGuo__ , @efssh , @pschwllr , @SchwallerGroup , @NCCR_Catalysis . arxiv.org/abs/2511.03112

See you there! 🤗

Our new work, “QCell: Comprehensive Quantum-Mechanical Dataset Spanning Diverse Biomolecular Fragments,” is now out on arXiv! 🌱 1/7

Exciting postdoc opportunity in the @SchwallerGroup at EPFL! We're hiring a postdoc to advance ML-driven synthesis planning after Zlatko Joncev’s successful exit to co-found B-12 (YC '25) 🚀 Work on: - LLMs for strategic synthesis planning - Chemical reasoning at scale - Building the next-gen framework for retrosynthesis Our recent preprint shows that LLMs can guide synthesis planning with natural-language strategies — combining AI reasoning with traditional chemical tools (arxiv.org/abs/2503.08537). Join us at the intersection of chemistry & AI. Up to 2 years. Based in Lausanne 🇨🇭 Apply: forms.fillout.com/t/nnxVE3Rc… #ChemTwitter #MachineLearning #SynthesisPlanning #PostdocPosition

You don’t like molecular dynamics? We get it. That’s why at this year’s LLM hackathon for Chemistry and Materials Science, we built not one, but ✨two✨ AI agents for molecular dynamics 👇

Our recent work on SO3LR, a general-purpose machine learned force field for molecular simulations, has been published in @J_A_C_S! 🌞

Introducing GRACE foundational machine learning interatomic potentials – a new SOTA Pareto front for accuracy vs. performance, built for efficient MD simulations, versatile fine-tuning & distillation. Learn more: arxiv.org/abs/2508.17936 & gracemaker.readthedocs.io/en… #MaterialsScience

AI4Mat is back for NeurIPS! time to crystallize those ideas and make a solid-state submission by august 22, 2025 💪 new this year: opt-in your work for our Research Learning from Speaker Feedback program -- a new structured discussion format where spotlight presenters receive curated, in-depth feedback from invited discussants 🧐 check out our website for more: sites.google.com/view/ai4mat… brought to you by a 🔥organizing committee: @MiretSantiago @anoopnm007 @SteMartiniani @kmjablonka @ADuvalinho Emily Jin Rocío Mercado Oropeza

b-12 (b12-labs.com) is building AI agents that help chemists design experiments and automatically run them on lab robots. They turn months of manual chemistry work into minutes of automated execution. Congrats on the launch @drecmb & @ZJoncev! ycombinator.com/launches/O3V…