MLFFs 🤝 Polymers — SimPoly works! Our team at @MSFTResearch AI for Science is proud to present SimPoly (SIM-puh-lee) — a deep learning solution for polymer simulation. Polymeric materials are foundational to modern life—found in everything from the clothes we wear and the food we consume to high-performance materials in aerospace, electronics, and medicine. Today, we introduce a new way to simulate them. We built a machine learning force field (MLFF) to predict macroscopic properties across a broad range of polymers—trained only on quantum-chemical data, with no experimental fitting. Specifically, we accurately compute polymer densities via large-scale MD simulations, achieving higher accuracy than classical force fields. We also capture second-order phase transitions, enabling prediction of glass transition temperatures. These two properties are fundamental to processing and application design. Finally, we created a benchmark based on experimental data for 130 polymers plus an accompanying quantum-chemical dataset—laying the foundation for a fully in silico design pipeline for next-generation polymeric materials. The incredible team: Jean Helie, @temporaer, Yicheng Chen, Guillem Simeon, @a_kzna, @ErnestoCheco, @erunzzz, Gabriele Tocci, @chc273, @yatao_li, @SherryLixueC, @zunwang_msr, Bichlien H. Nguyen, Jake A. Smith, and Lixin Sun. 📄 Preprint: arxiv.org/abs/2510.13696 ⚙️ Data and code release: in progress⏳ #MLFFs #Polymers #AIforScience #DeepLearning #SimPoly #ScientificML #Microsoft #MicrosoftResearch #MicrosoftQuantum

I'm incredibly proud of what John has accomplished during his internship. Take a look!

Extremely excited to be sharing the output of my internship in @MSFTResearch's #AIForScience team: "Understanding multi-fidelity training of machine-learned force-fields" 🤖🧪

We are looking for a senior ML engineer to help the team push the boundaries of scientific innovation. Please apply if you are passionate about building new and impactful solutions #buidl #ai4science #aiforscience #chemjob #ai4chemistry #ai4materials jobs.careers.microsoft.com/g…

Excited to introduce Aurora: a foundation model of the atmosphere.  In <1min, Aurora produces 5-day global air pollution predictions and 10-day high-resolution weather forecasts that outperform SOTA classical simulation tools and the best specialized deep learning models… 1/n

[1/N] Generative AI has revolutionized how we create text and images. How about designing novel materials? We at @MSFTResearch #AI4Science are thrilled to announce MatterGen: our generative model that enables broad property-guided materials design. 👇 arxiv.org/abs/2312.03687

📢New internship opening at AI4Science in Amsterdam or Berlin!📢 For our interdisciplinary team working on electronic structure and deep learning, we are looking for someone to join us and work on synthetic data generation and curation. Please apply here! jobs.careers.microsoft.com/g…

Interested in accelerating scientific discovery with AI? Join our interdisciplinary global team! Two exciting opportunities for engineers: Amsterdam or Berlin: jobs.careers.microsoft.com/g… Beijing: jobs.careers.microsoft.com/g…

For those of you interested in molecular design, our docking package "dockstring" is now easier to install than ever! Just type "conda install -c conda-forge dockstring" or "pip install dockstring" to start calculating docking scores! @gncsimm @jmhernandez233

Happy that we can finally share our codebase. Thanks to @rejuvyesh and @djjruhe :) Geometric layers will be included soon. microsoft.github.io/clifford…

Excited to opensource PDEArena: a modern, scalable PDE surrogate learning framework. With over 20 models and many different PDE tasks. Blog: microsoft.com/en-us/research… Website: microsoft.github.io/pdearena… Paper: arxiv.org/abs/2209.15616 Authors: @rejuvyesh, @jo_brandstetter 1/n

Join @MSFTResearch lab in Amsterdam! We look for a senior researcher with expertise in method development (theory & implementation) in electronic structure (DFT/1RDMFT and/or ab initio methods). Deep science in a great collaborative environment! #compchem careers.microsoft.com/us/en/…

We have a new opening for a senior research engineer in our AI4Science team @MSFTResearch in Amsterdam: careers.microsoft.com/us/en/… Please spread the word and apply if you're interested!

DOCKSTRING: Easy Molecular #Docking Yields Better Benchmarks for Ligand Design #DrugDesign #DrugDiscovery pubs.acs.org/doi/10.1021/acs… @MiguelMachuque1 @gncsimm @austinjtripp @jmhernandez233 @AndreasBenderUK #current_issue #JCIM #MachineLearning #DeepLearning

Microsoft Research announces AI4Science, a new global team of machine learning, quantum physics, computational chemistry, molecular biology, fluid dynamics, and software engineering experts working to tackle important societal challenges. Learn more: msft.it/6016bIoWj

Efficient higher order message passing is all you need! With @IlyesBatatia, @davkovacs10, Christoph Ortner, and Gabor Csanyi.

🚀⚡️Ever wondered wondered what is the relationship between the plethora of equivariant MPNN methods recently published for fitting potential energies? Here we present a practical framework addressing just that! NequIP, ACE, SOAP, EGNN etc. arxiv.org/abs/2205.06643 Details:👇👇

We're excited to present our paper "Symmetry-Aware Actor-Critic for 3D Molecular Design" at #ICLR2021 w/ @gncsimm, Gábor Csányi, @jmhernandez233 Join us: Monday, 3 May 2021, 17:00-19:00 (GMT 1) at iclr.cc/virtual/2021/poster/… ICYMI, check out our blog post: mlg-blog.com/2021/04/30/rein…

ML for molecular design needs to move beyond graphs! Check out our new blog post to learn how we use reinforcement learning and quantum chemistry to build molecules directly in Cartesian coordinates: mlg-blog.com/2021/04/30/rein… w/ @gncsimm Sounds cool? Talk to us at #ICLR2021.