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Robert Pinsler

@rpinsler

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

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25.11.2024
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Latest posts by Robert Pinsler @rpinsler

Senior Data Engineer: t.co/qwEJi6ud6F
Senior RSDE / ML Engineer: t.co/gTzfNSeIqv
Senior Applied Scientist: t.co/SC1O5QUIQt

Please share with anyone who might be interested. Feel free to reach out if you have any questions.

05.03.2026 10:20 πŸ‘ 1 πŸ” 0 πŸ’¬ 0 πŸ“Œ 0

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 ⬇️

05.03.2026 10:20 πŸ‘ 5 πŸ” 2 πŸ’¬ 1 πŸ“Œ 2

Skala is now available to everyone!
Why are we releasing it? Because we’re not just aiming to publish a cool paper β€” 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

09.10.2025 16:46 πŸ‘ 38 πŸ” 13 πŸ’¬ 1 πŸ“Œ 0

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

10.10.2025 10:58 πŸ‘ 0 πŸ” 0 πŸ’¬ 0 πŸ“Œ 0
End-to-end data-driven weather prediction - Nature Nature - End-to-end data-driven weather prediction

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...

20.03.2025 17:22 πŸ‘ 5 πŸ” 3 πŸ’¬ 0 πŸ“Œ 0
GitHub - microsoft/bioemu-benchmarks: Benchmarking code accompanying the release of `bioemu` Benchmarking code accompanying the release of `bioemu` - microsoft/bioemu-benchmarks

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...

21.02.2025 15:49 πŸ‘ 76 πŸ” 21 πŸ’¬ 4 πŸ“Œ 0
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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...

19.02.2025 16:08 πŸ‘ 14 πŸ” 8 πŸ’¬ 0 πŸ“Œ 2
Emulation of protein equilibrium ensembles with generative deep learning | JosΓ© JimΓ©nez Luna, Yu Xie
Emulation of protein equilibrium ensembles with generative deep learning | JosΓ© JimΓ©nez Luna, Yu Xie YouTube video by VantAI

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...

17.02.2025 09:23 πŸ‘ 34 πŸ” 14 πŸ’¬ 0 πŸ“Œ 1
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⭐️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 πŸ™ƒ (audio on)

11.02.2025 18:33 πŸ‘ 12 πŸ” 3 πŸ’¬ 1 πŸ“Œ 2

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!

16.01.2025 21:58 πŸ‘ 7 πŸ” 3 πŸ’¬ 1 πŸ“Œ 0

Super excited to share that MatterGen is published in Nature!

16.01.2025 13:55 πŸ‘ 7 πŸ” 2 πŸ’¬ 0 πŸ“Œ 0

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

16.01.2025 13:08 πŸ‘ 10 πŸ” 4 πŸ’¬ 0 πŸ“Œ 0

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

16.01.2025 10:26 πŸ‘ 17 πŸ” 10 πŸ’¬ 0 πŸ“Œ 0

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.

16.01.2025 10:10 πŸ‘ 12 πŸ” 9 πŸ’¬ 1 πŸ“Œ 0

#compchem

16.01.2025 12:18 πŸ‘ 20 πŸ” 6 πŸ’¬ 0 πŸ“Œ 0
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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...

16.01.2025 13:21 πŸ‘ 4 πŸ” 3 πŸ’¬ 0 πŸ“Œ 0

πŸ“’ Paper + code release πŸ“ƒπŸ’»

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...

16.01.2025 10:15 πŸ‘ 79 πŸ” 21 πŸ’¬ 2 πŸ“Œ 1

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...

16.01.2025 13:33 πŸ‘ 4 πŸ” 2 πŸ’¬ 0 πŸ“Œ 0

Thanks for your kind words. It has been a lot of work to open-source this (e.g., due to compliance). Nowadays, people in the community are quick to judge if you don't open-source immediately, so I really appreciate that you don't just take this for granted!

16.01.2025 13:24 πŸ‘ 2 πŸ” 0 πŸ’¬ 0 πŸ“Œ 0
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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

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.

πŸ’»
github.com/microsoft/ma...
πŸ“„
arxiv.org/abs/2312.03687
πŸ“„πŸ“„
arxiv.org/abs/2405.04967

11.12.2024 06:39 πŸ‘ 19 πŸ” 6 πŸ’¬ 1 πŸ“Œ 0

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

09.12.2024 15:11 πŸ‘ 18 πŸ” 4 πŸ’¬ 0 πŸ“Œ 1
Preview
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...

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

09.12.2024 02:19 πŸ‘ 83 πŸ” 27 πŸ’¬ 4 πŸ“Œ 1

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

06.12.2024 12:14 πŸ‘ 5 πŸ” 2 πŸ’¬ 0 πŸ“Œ 0
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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...

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...

06.12.2024 08:22 πŸ‘ 65 πŸ” 15 πŸ’¬ 2 πŸ“Œ 0
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hi everyone!! let's try this optimal transport again πŸ™ƒ

05.12.2024 12:58 πŸ‘ 328 πŸ” 31 πŸ’¬ 2 πŸ“Œ 0

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

06.12.2024 13:13 πŸ‘ 9 πŸ” 1 πŸ’¬ 0 πŸ“Œ 0
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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...

06.12.2024 08:38 πŸ‘ 442 πŸ” 147 πŸ’¬ 21 πŸ“Œ 29

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

04.12.2024 14:06 πŸ‘ 4 πŸ” 3 πŸ’¬ 0 πŸ“Œ 0

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

03.12.2024 21:10 πŸ‘ 9 πŸ” 3 πŸ’¬ 0 πŸ“Œ 0
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

🚨Our Machine Learning Force Field Mattersim is now available! 🚨

Check it out here πŸ‘‡
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!

03.12.2024 17:11 πŸ‘ 81 πŸ” 25 πŸ’¬ 5 πŸ“Œ 2