@zany_cloud

Applying machine learning to materials science. Principal Researcher at @MSFTResearch Views are my own https://xitter.cf/t.co/yJVaUUuIk3

 Cambridge
Joined October 2021
  • Tweets278
  • Following261
  • Followers834
23Media
📢 Paper + code release 📃💻 After 2 years of work, I'm excited to announce our newest paper, MatterGen, has been published in Nature! nature.com/articles/s41586-0…
Microsoft Research
@MSFTResearch16 Jan 2025
Microsoft researchers introduce MatterGen, a model that can discover new materials tailored to specific needs—like efficient solar cells or CO2 recycling—advancing progress beyond trial-and-error experiments. msft.it/6012U8zX8
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Frank Noe@FrankNoeBerlinOct 20
Public preview of BioEmu2! @MSFTResearch AI for Science’s new foundation model for biomolecular structure, dynamics and function. Open weights, MIT license. github.com/microsoft/bioemu2 Movie: BioEmu2-simulated binding of intrinsically disordered peptide PUMA to MCL-1 receptor. 🧵⬇️
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Custom-made molecules are advancing medicine, materials, and agriculture, but producing them is slow and expensive. A new Nature paper highlights RetroChimera, a predictive model that helps accelerate chemical synthesis, helping researchers explore a wide range of molecules.: msft.it/6012a5Ogy
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Marwin Segler@marwinseglerSep 21
Synthesis is a major bottleneck in drug discovery. AI synthesis planning can help propose better routes and make generative molecular design tractable. With our retroChimera model we have been pushing the boundaries of these models further - out in @Nature today. 1/2
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Skala 1.1, the updated deep-learning exchange-correlation functional from Microsoft Research, provides greater accuracy, expanded accessibility across the computational chemistry ecosystem, and a living benchmark to track computational performance. msft.it/6011aOXe5
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Frank Noe@FrankNoeBerlinAug 25
We are hiring a postdoc on very large-scale protein modeling and free energy calculation for protein-ligand and membrane protein systems. Join us at @MSFTResearch to develop the next generation of AI models for biomolecular dynamics and function. apply.careers.microsoft.com/…

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Aurora 1.5 adds 22 more variables, hourly temporal resolution, and probabilistic ensemble forecasting to the Aurora foundation model, making it more useful for real-world weather, climate, and energy applications. msft.it/6017vInGR
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Going to @icmlconf this week, looking for exciting ML / Materials research. If you want to chat, you can find me at the @MSFTResearch booth on Wednesday at 16:00.
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Join us at @MSFTResearch AI for science and work on exciting Materials Design challenges! This is a 2-year Machine Learning post-doc position within the team. Location: Cambridge (UK), Berlin (DE), or Amsterdam (NL). Link in comments below 👇
Robert Pinsler@rpinslerJun 3
Our team at @MSFTResearch is looking for a 2y ML post-doc to re-think materials design using AI. This is an exceptional opportunity to join our ambitious mission of solving some of the most pressing challenges that exist today. #ai4science #materials ⬇️See link below ⬇️
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apply.careers.microsoft.com/…

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Robert Pinsler@rpinslerJun 3
Our team at @MSFTResearch is looking for a 2y ML post-doc to re-think materials design using AI. This is an exceptional opportunity to join our ambitious mission of solving some of the most pressing challenges that exist today. #ai4science #materials ⬇️See link below ⬇️
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Frank Noe@FrankNoeBerlinJun 3
Postdoc openings on experimental data integration integration into BioEmu-next, focusing on cryo-EM and binding affinities. Join us at @MSFTResearch Cambridge or Berlin. #AI #MachineLearning #Protein #Biology apply.careers.microsoft.com/…

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MatterSim now faster than ever, and with LAMMPS support for your multi-GPU simulations
Robert Pinsler@rpinslerMay 12
Replying to @rpinsler
⚡️ Faster simulation: We have accelerated MatterSim-v1 model inference by 3-5x and integrated it with the LAMMPS software package, enabling large-scale simulations across multiple GPUs. (4/6)
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Robert Pinsler@rpinslerMay 12
Excited to announce major #MatterSim updates! 👩‍🔬 Experimentally synthesized high thermal conductor identified by MatterSim ⚡️ 3-5x inference speed-up 💪 MatterSim-MT: a new multi-task foundation model for in silico materials characterization ⬇️ Details below (1/6)
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MatterSim is expanding what AI can do for materials science—from faster large-scale simulations to MatterSim-MT, a new multi-task model for simulating properties beyond potential energy surfaces alone. msft.it/6017vPamT
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Prof. Amir Karton@Lab_initioApr 23
I'm thrilled that the new #deeplearning #DFT Skala-1.1 functional is out! arxiv.org/abs/2506.14665 Skala-1.1 breaks the longstanding accuracy-to-cost trade-off of Jacob's Ladder. Amazing collaboration with @paolagorigiorgi and the entire @MSFTResearch AI4Science team! #CompChem
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The latest release of Skala is out! Accuracy largely improved beyond hybrids at semilocal cost! #compchem
Rianne van den Berg@vdbergrianneApr 22
Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala

Accurate and scalable exchange-correlation with deep learning

Density Functional Theory (DFT) underpins much of modern computational chemistry and materials science. Yet, the reliability of DFT-derived predictions of experimentally measurable properties...

arxiv.org
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Chin-Wei Huang@chinwei_hApr 22
Exciting new update of Skala. This table should speak for itself: Skala is now the leading density functional in main-group chemistry surpassing previous SOTA hybrid functional at a cheaper, semi-local cost. #compchem #ai4science
Rianne van den Berg@vdbergrianneApr 22
Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala

Accurate and scalable exchange-correlation with deep learning

Density Functional Theory (DFT) underpins much of modern computational chemistry and materials science. Yet, the reliability of DFT-derived predictions of experimentally measurable properties...

arxiv.org
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Today we're sharing a major Skala update: new paper and model release. Skala is a deep-learned XC functional for DFT: 2.8 kcal/mol on GMTKN55, wins 32/55 subsets & surpasses SOTA hybrids in accuracy at semi-local cost. Paper: arxiv.org/abs/2506.14665 Code: github.com/microsoft/skala

Accurate and scalable exchange-correlation with deep learning

Density Functional Theory (DFT) underpins much of modern computational chemistry and materials science. Yet, the reliability of DFT-derived predictions of experimentally measurable properties...

arxiv.org
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If you are interested in AI, materials science, and working on hard problems with an amazing team, this is the place for you.
Robert Pinsler@rpinslerMar 5
We are significantly expanding to accelerate our ambitious plans for AI-driven materials discovery at @MSFTResearch AI for Science. Looking for a Data Engineer, ML Engineer and Applied Scientist (UK/NL/DE). ⬇️See job postings below ⬇️
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Claudio Zeni retweeted
Robert Pinsler@rpinslerMar 5
We are significantly expanding to accelerate our ambitious plans for AI-driven materials discovery at @MSFTResearch AI for Science. Looking for a Data Engineer, ML Engineer and Applied Scientist (UK/NL/DE). ⬇️See job postings below ⬇️
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