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Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge | JACS #JACSPerspective Frank Glorius Glorius Group Universität Münster Total Synthesis and Methodology Highlights The Grzybowski Group #AI #Retrosynthesis #Expert #Knowledge pubs.acs.org/doi/10.1021/ja…

📢PhD Position Alert📢 I'm on the lookout for PhD students to join my group Bergische Universität Wuppertal – please spread the word! And if you're a MSc student excited about digitizing (organic) chemistry labs, I'd love to hear from you! ➡️fsk-lab.github.io #PhDPostions #ChemTwitter

We are thrilled to introduce "Late-Stage Saturation" (LSS) 👨🏽‍🔬 Partnering with Jiajia Ma Group and Tim Cernak enabled us to develop a tool to lift complex molecules into the third dimension. 🇺🇸🇨🇳🇩🇪 Michigan Chemistry J. Am. Chem. Soc. @PharmaCampus_MS pubs.acs.org/doi/10.1021/ja…

Have you ever struggled to select the right substrates for your scope? 😯 Check out our publication in ACS Central Science for an answer! 🤗 doi.org/10.1021/acscen…

"Dear Frank, I just tried out your programme on a molecule a few seconds ago. Very interesting and useful." EnTdecker (Discoverer)🚀: Machine Learning-Based Platform for Guiding Substrate Discovery in Energy Transfer Photocatalysis Just online J. Am. Chem. Soc. pubs.acs.org/doi/full/10.10…

Trying to find substrates for EnT catalysis 💡? The Glorius Group presents EnTdecker - a ML tool to predict triplet energies and spin densities of organic molecules. Congratulations to the team! 👏🏻 #molecular #machinelearning

Girl's and Boy's Day 2024🧒😃: many interested pupils had the opportunity to gain an insight into the projects of the SPP 2363 at the Chair of Theoretical Chemistry II (Prof. Jörg Behler) at Ruhr-Universität Bochum. 👏

Evolutionary Algorithm for Interpretable Molecular Representations 🐒🧑‍🔬💻- funded by DFG public | @[email protected] SPP 2363 & published in Chem : doi.org/10.1016/j.chem… Great team effort by Glorius Group & Herbert Kuchen 👏🍾😀 highlighted in this press release: uni-muenster.de/news/view.php?…

Our Cover of Chem 📰 (Machine Learning - Random Forest - Molecular Fingerprints - Evolutionary Algorithm) - hope you like it! cell.com/chem/current Chem Universität Münster Department of Chemistry and Pharmacy, Münster SPP 2363 DFG public | @[email protected]

Looking back at a great PhD Workshop in beautiful Münster! 🚲☀️ Two days of inspiring presentations and excellent discussions while reconnecting with old and new friends. #PhDLife #SPP2363

🚀 Exciting news from two talented SPP2363 students: together with two other PhD students and an economy adviser they’ve launched AI-Driven Therapeutics! They develop a co-scientist for protein design 🧑‍🔬💻🧪 🌐 ai-dt.de #SPP2363 #Startup #Innovation

We SPP 2363 are delighted to unveil the lineup for the 7⃣th International Mini-Symposium on #Molecular #MachineLearning 🧪🤖, 16 Jan, 2025: ✨the Kulik Group ✨Fernanda Duarte ✨Bingqing Cheng ✨Sigman Lab 📄More info: bit.ly/info7thMML 💻Free registration: bit.ly/7thMML

❗️Join tomorrow for our #7thMML Molecular #MachineLearning online symposium and learn about how machine learning helps to shape the future of chemistry!🌟 ✅Register for free: bit.ly/7thMML

Live and on-air! 🎙️ bit.ly/7thMML #7thMML #Molecular #MachineLearning #Symposium

How can #MachineLearning accelerate the discovery of transition metal-containing materials? 🎤Heather J. Kulik (the Kulik Group) is kicking off the #7thMML Symposium! 🧪 “Getting from the Computer to Real World Materials Faster with Machine Learning”

Solvent effects? Reaction dynamics? 🔄🌊 Fernanda Duarte (Fernanda Duarte) is now on stage at the #7thMML Symposium discussing how #MachineLearning Potentials (MLPs) balance efficiency & accuracy in modeling chemical reactions in solution! 🧪🤖

Need to predict material properties? 🔮🧪 Bingqing Cheng is now presenting at the #7thMML #Symposium! Learn how she combines statistical mechanics & #MachineLearning interatomic potentials to compute phase diagrams, chemical potentials, and reactions on surfaces! 🤖✨

How can data science & #MachineLearning transform reaction optimization? 🤖🧪 Matt Sigman (Sigman Lab) wraps up the #7thMML #Symposium with a deep dive into tools for analyzing structure-function relationships, optimizing reactions, and designing smarter experiments! 🧠✨

That’s a wrap!🏁 A huge THANK YOU to our incredible speakers and everyone who joined us for the 7th International #Symposium on #Molecular #MachineLearning!🙌✨ Stay tuned for more exciting updates in the world of #MachineLearning & #Chemistry. See you at the #8thMML edition!

The Glorius Group is calling for a passionate postdoc who wants to shape the future of digital chemistry – where ML models, mass spectrometry, and human insight meet. ⚗️💻😀 In collaboration with: lab25, ChemInnovation 🚀 🙏 RT #chemistry Jobposting: stellen.uni-muenster.de/jobposting/4e9…