We are significantly expanding to accelerate our ambitious plans for AI-driven materials discovery at @msftresearch.bsky.social AI for Science. Looking for a Data Engineer, ML Engineer and Applied Scientist (UK/NL/DE). ⬇️ See job postings below ⬇️

Skala is now available to everyone! Why are we releasing it? Because we’re not just aiming to publish a cool paper — we’re on a mission to bring DFT to chemical accuracy using deep learning. And to make real progress, we need the community’s feedback. #compchem

Job alert! Check out our open roles (Senior Researcher, Senior Applied Scientist, Senior Data Engineer) for AI for materials discovery.

Incredibly excited to see that Aardvark-Weather is finally out in Nature!! An amazing project with a truly fantastic team. The lead authors Anna Allen and Stratis Markou have worked really really hard to make this project happen. www.nature.com/articles/s41...

Today we have published BioEmu-Benchmarks (MIT license): a code to evaluate the multi-conformation sampling benchmarks, MD free energy landscape benchmarks, and folding free energy benchmarks shown in the BioEmu-1 paper with BioEmu or your own model. Some details below 🧵 github.com/microsoft/bi...

Nature published Microsoft research detailing our WHAM, an AI model that generates video game visuals & controller actions. We're releasing the model weights, sample data & WHAM Demonstrator on Azure AI Foundry to enable researchers to build on this work. www.microsoft.com/en-us/resear...

Check out this great BioEmu talk by @jjimenezluna.bsky.social and @yuxie.bsky.social in the VantAI lecture series. Thank you for hosting @mmbronstein.bsky.social @lucanaef.bsky.social www.youtube.com/watch?v=8vsT...

⭐️MatterGen has reached 1K stars on GitHub⭐️ Thanks for giving it a try, we look forward to seeing what you can discover with it! This is what we discovered so far 🙃 (audio on)

Excited to share the news that MatterGen is published on Nature today. Since the publication of our preprint, we have bee busy improving our evaluation; we have also shown successful exp synthesis! Grateful for the team members for their hard work and perseverance, and #MSR colleagues for support!

Super excited to share that MatterGen is published in Nature!

MatterGen now published in Nature 🔥 Very strong work from the materials team at MSR AI for Science!

Super excited to share that the MatterGen code is now public on GitHub! github.com/microsoft/ma...

Excited to finally announce the publication of MatterGen on Nature. MatterGen represents a new paradigm of materials design with generative AI. We are releasing the code of MatterGen under MIT license. Look forward to seeing how the community will use the tool and build on top of it.

A new diffusion-driven model called MatterGen generates stable inorganic crystals by refining random atom placements. Zeni et al. show it can be steered toward specific properties, opening efficient pathways for materials design. www.nature.com/articles/s41...

📢 Paper + code release 📃💻 After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature! www.nature.com/articles/s41... We are also releasing all the training data, model weights, model code, and evaluation code on GitHub! github.com/microsoft/ma...

MatterGen is out in Nature! MatterGen is a SOTA generative model for materials design. We also raise the bar for evaluation by considering compositional disorder and experimentally validating model capabilities. Code is open-source! www.nature.com/articles/s41... github.com/microsoft/ma...

Excited to talk about MatterGen and MatterSim (now on GitHub!) today at the @cecamevents.bsky.social l workshop at CECAM-HQ in EPFL Lausanne. If you're interested, drop by at 11.15, or let's chat afterwards. 💻 github.com/microsoft/ma... 📄 arxiv.org/abs/2312.03687 📄📄 arxiv.org/abs/2405.04967

Another great model from @msftresearch.bsky.social AI for Science - CHIMERA, an accurate retrosynthesis prediction model by @marwinsegler @MaziarzKris and team!

new preprint on chemical synthesis ML models - showing how to combine multiple models in a principled way - modern Transformers + GNN to featurize chemical reaction: - new insights in where the models shine + bonus: find the quirky named reaction! Feedback welcome! arxiv.org/abs/2412.05269

Exciting stuff! will be interesting to test this on our own favourite protein ensembles!

Excited to present what we've been up to the last couple years. Introducing BioEmu, a Biomolecular Emulator of protein dynamics: www.biorxiv.org/content/10.1...

hi everyone!! let's try this optimal transport again 🙃

Great progress from @franknoe.bsky.social and collaborators on the protein conformational sampling problem using AI!

Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science. www.biorxiv.org/content/10.1...

If you are at #F24MRS in Boston today, check out Tian's talk at symposium MT04 at 1:30pm. He will present our efforts to build AI tools for materials design at @msftresearch.bsky.social AI for Science. #materialsscience #machinelearning #mattergen #mattersim

Major announcement from Microsoft, their machine learning matter simulator is now available

🚨Our Machine Learning Force Field Mattersim is now available! 🚨 Check it out here 👇 msft.it/6013oBZLt The force field is designed to be used on a vast range of temperatures and pressures, try it yourself :) Feedback and suggestions are very welcome!