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Robert Pinsler

@rpinsler.bsky.social
71 followers 99 following 5 posts

AI for materials design at Microsoft Research AI for Science | Prev. University of Cambridge. Views are my own.

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Robert Pinsler @rpinsler.bsky.social · 05/03/2026
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 ⬇️
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Paola Gori Giorgi @paolagorigiorgi.bsky.social · 09/10/2025
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
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Robert Pinsler @rpinsler.bsky.social · 10/10/2025
Job alert! Check out our open roles (Senior Researcher, Senior Applied Scientist, Senior Data Engineer) for AI for materials discovery.
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Wessel @wessel.ai · 20/03/2025
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...
nature.com
End-to-end data-driven weather prediction - Nature
Nature - End-to-end data-driven weather prediction
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Frank Noe @franknoe.bsky.social · 21/02/2025
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...
github.com
GitHub - microsoft/bioemu-benchmarks: Benchmarking code accompanying the release of `bioemu`
Benchmarking code accompanying the release of `bioemu` - microsoft/bioemu-benchmarks
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Microsoft Research @msftresearch.bsky.social · 19/02/2025
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...
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Frank Noe @franknoe.bsky.social · 17/02/2025
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...
youtube.com
Emulation of protein equilibrium ensembles with generative deep learning | José Jiménez Luna, Yu Xie
YouTube video by VantAI
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Claudio Zeni @claudiozeni.bsky.social · 11/02/2025
⭐️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)
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Ryota Tomioka @ryotat.bsky.social · 16/01/2025
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!
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Bas Veeling @basv.bsky.social · 16/01/2025
Super excited to share that MatterGen is published in Nature!
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Krzysztof Maziarz @maziarz.bsky.social · 16/01/2025
MatterGen now published in Nature 🔥 Very strong work from the materials team at MSR AI for Science!
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Daniel Zuegner @danielzuegner.bsky.social · 16/01/2025
Super excited to share that the MatterGen code is now public on GitHub! github.com/microsoft/ma...
github.com
GitHub - microsoft/mattergen: Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards...
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c...
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Tian Xie @xie-tian.bsky.social · 16/01/2025
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.
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Marwin Segler @marwinsegler.bsky.social · 16/01/2025
#compchem
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Jorge Bravo Abad @bravo-abad.bsky.social · 16/01/2025
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...
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Claudio Zeni @claudiozeni.bsky.social · 16/01/2025
📢 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...
github.com
GitHub - microsoft/mattergen: Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards...
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c...
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Robert Pinsler @rpinsler.bsky.social · 16/01/2025
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...
github.com
GitHub - microsoft/mattergen: Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards...
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property c...
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Claudio Zeni @claudiozeni.bsky.social · 11/12/2024
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
github.com
GitHub - microsoft/mattersim: MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
MatterSim: A deep learning atomistic model across elements, temperatures and pressures. - microsoft/mattersim
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Frank Noe @franknoe.bsky.social · 09/12/2024
Another great model from @msftresearch.bsky.social AI for Science - CHIMERA, an accurate retrosynthesis prediction model by @marwinsegler @MaziarzKris and team!
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Marwin Segler @marwinsegler.bsky.social · 09/12/2024
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
arxiv.org
Chimera: Accurate retrosynthesis prediction by ensembling models with diverse inductive biases
Planning and conducting chemical syntheses remains a major bottleneck in the discovery of functional small molecules, and prevents fully leveraging generative AI for molecular inverse design. While ea...
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Ronnie Berntsson @rberntsson.bsky.social · 06/12/2024
Exciting stuff! will be interesting to test this on our own favourite protein ensembles!
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Jose Jimenez-Luna @jjimenezluna.bsky.social · 06/12/2024
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...
biorxiv.org
Scalable emulation of protein equilibrium ensembles with generative deep learning
Following the sequence and structure revolutions, predicting the dynamical mechanisms of proteins that implement biological function remains an outstanding scientific challenge. Several experimental t...
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Brandon Amos @bdamos.bsky.social · 05/12/2024
hi everyone!! let's try this optimal transport again 🙃
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Alán Aspuru-Guzik @aspuru.bsky.social · 06/12/2024
Great progress from @franknoe.bsky.social and collaborators on the protein conformational sampling problem using AI!
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Frank Noe @franknoe.bsky.social · 06/12/2024
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...
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Claudio Zeni @claudiozeni.bsky.social · 04/12/2024
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
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Robert Palgrave @robertpalgrave.bsky.social · 03/12/2024
Major announcement from Microsoft, their machine learning matter simulator is now available
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Claudio Zeni @claudiozeni.bsky.social · 03/12/2024
🚨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!
msft.it
GitHub - microsoft/mattersim: MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
MatterSim: A deep learning atomistic model across elements, temperatures and pressures. - microsoft/mattersim
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