Daniel Zuegner
@danielzuegner.bsky.social
Senior Researcher @msftresearch.bsky.social #AI for #Science. Past: PhD @ TUM, internships @ Amazon AWS, Spotify. Amateur Photographer in my free time.
Check out these exciting news about our MatterSim model!
Claudio Zeni@claudiozeni.bsky.social · 3mo ago#MatterSim keeps getting better! 👩🔬 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) #materials #mlip #lammps
#MatterSim keeps getting better! 👩🔬 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) #materials #mlip #lammps
I'm excited rto attend ICLR in Rio this week. Hit me up if you'd like to meet up for coffee! I will also be at the @msftresearch.bsky.social booth to talk about MSR AI for Science on Thu 12-12:30pm, Fri+Sat 10-10:30am. See you there!
Come work with us on AI-driven materials discovery at @msftresearch.bsky.social!
Robert Pinsler@rpinsler.bsky.social · 5mo agoWe 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 ⬇️
Come work with us in the materials team at @msftresearch.bsky.social AI for Science!
Tian Xie@xie-tian.bsky.social · 10mo ago🚨We are hiring! 🚨 Want to join a highly talented, collaborative team and build the next frontier model for materials design? Apply to the following roles and join our materials team at @msftresearch.bsky.social AI for Science. Location can be Cambridge UK or Amsterdam NL or Berlin DE.
Come work with us at @msftresearch.bsky.social in the team behind MatterGen and MatterSim!
Tian Xie@xie-tian.bsky.social · last yr.Want to join our efforts @msftresearch.bsky.social AI for Science to push the frontier of AI for materials? We are the team behind MatterGen & MatterSim and we have 2 job openings! Each can be in Amsterdam, NL, Berlin, DE, or Cambridge, UK.
Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, green fertilizers, precision drug discovery, and more. www.microsoft.com/en-us/resear...
Very excited and proud of this incredible team effort!
Microsoft Research@msftresearch.bsky.social · last yr.Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, green fertilizers, precision drug discovery, and more. www.microsoft.com/en-us/resear...
🚀 After two+ years of intense research, we’re thrilled to introduce Skala — a scalable deep learning density functional that hits chemical accuracy on atomization energies and matches hybrid-level accuracy on main group chemistry — all at the cost of semi-local DFT ⚛️🔥🧪🧬
Thermal conductivity is critical in modern electronics, but in a post-Moore’s Law world, the need for novel structures that surpass the heat transfer properties of silicon is essential. Learn how AI is helping scientists discover these next-gen materials. msft.it/6013SnPAN
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 - microsoft/bioemu-benchmarks: Benchmarking code accompanying the release of `bioemu`
Benchmarking code accompanying the release of `bioemu` - microsoft/bioemu-benchmarks
github.com
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...
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...
Emulation of protein equilibrium ensembles with generative deep learning | José Jiménez Luna, Yu Xie
YouTube video by VantAI
youtube.com
The BioEmu-1 model and inference code are now public under MIT license!!! Please go ahead, play with it and let us know if there are issues. github.com/microsoft/bi...
GitHub - microsoft/bioemu: Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning
Inference code for scalable emulation of protein equilibrium ensembles with generative deep learning - microsoft/bioemu
github.com
Frank Noe@franknoe.bsky.social · 2y agoSuper 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...
Meet BioEmu-1 from Microsoft Research. This deep learning model can generate thousands of protein structures per hour, unlocking new possibilities for protein scientists and drug discovery and research. www.microsoft.com/en-us/resear...
MatterGen now published in Nature 🔥 Very strong work from the materials team at MSR AI for Science!
Microsoft Research@msftresearch.bsky.social · 2y agoMicrosoft 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. www.microsoft.com/en-us/resear...
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.
Microsoft Research@msftresearch.bsky.social · 2y agoMicrosoft 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. www.microsoft.com/en-us/resear...
Super excited to share that the MatterGen code is now public on GitHub! github.com/microsoft/ma...
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...
github.com
Microsoft Research@msftresearch.bsky.social · 2y agoMicrosoft 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. www.microsoft.com/en-us/resear...
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. www.microsoft.com/en-us/resear...
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 - 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
github.com
🚨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!
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
msft.it
“Expected Hierarchical Clustering” is at #NeurIPS2024! This would not have been possible without Marcel Kollovieh* who lead the project, @danielzuegner.bsky.social and Stephan Günnemann ! 1/4
🎉Excited to announce major new breakthroughs in our Aurora foundation model! Our team (@cbodnar.com, @wessel.ai, @megstanley.bsky.social, @a-lucic.bsky.social, Anna Vaughan) has achieved unprecedented results across multiple Earth system forecasting tasks. Here's what's new... 🧵
We are glad to announce that we are releasing MatterSim-V1 for public use today. We look forward to hearing your feedback after trying out our models. We are actively working on developing more pre-trained models for MatterSim. Please stay tuned for updates.
Claudio Zeni@claudiozeni.bsky.social · 2y ago🚨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!
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...
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...
biorxiv.org
Check out BioEmu, the latest and greatest coming out of Microsoft Research AI for Science!
Frank Noe@franknoe.bsky.social · 2y agoSuper 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...