SPP 2363 Molecular Machine Learning | Developing ML solutions for molecular problems | Interdisciplinary and collaborative Priority Program funded by the DFG
Joined March 2022
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SPP 2363 retweeted
Congratulations to Felix Katzenburg (@FKatzenburg )🐈⬛🏰 on successfully defending his PhD! 🎓 🥂 🏆 We're incredibly happy to have been part of this journey, and wish you all the best for your next chapter at Alán Aspuru-Guzik's group!
#PhDone
SPP 2363 retweeted
Thrilled to share our hybrid inverse design strategy for discovering organic photocatalysts, now published in @JACS: Accelerating EnT catalyst discovery by bridging generative modeling and experimental validation.
pubs.acs.org/doi/10.1021/jac…
SPP 2363 retweeted
🚀 Our Mini-Symposium on Molecular Machine Learning returns for its 8th Edition! 🤖 💻
🔗Register here: uni-ms.zoom-x.de/webinar/reg…
🗓 Date: January 15th, 2026
🕒 Time: 3:00 PM (UTC+1)
💻 Location: Online | Free of charge
#MachineLearning #Chemistry #DataScience #SPP2363
SPP 2363 retweeted
8th Molecular Machine Learning Symposium - ONLINE!
15th Jan 2026, 3pm UTC+1 - Safe the date!
More information to follow shortly...
Registration link:
uni-ms.zoom-x.de/webinar/reg…
SPP 2363 retweeted
Richard Willstätter Lecture by Ilan Marek, Technion
Excellent talk about non-classical carbocations, followed by presentation from PhD student Noam Orbach on housanes. 👏😀👏This concludes @GDCh_aktuell lecture tour (Freiburg, Munich and Muenster).
en.gdch.de/gdch/prizes-and-a…
SPP 2363 retweeted
Liebig-Lecturer 2025: Prof. Renana Gershoni-Poranne
Award by @GDCh_aktuell. Lecture tour ongoing, talk @uni_muenster was a blast:
Mission ImPASsible: Decoding Polycyclic Aromatic Systems with Deep Learning 👍 🖥️ 😊
@PoranneG with team MolMachLearning of @GloriusGroup @spp2363
Creativity is the engine of discovery ✨ Fantastic PhD workshop with @ilona_lipp on strategies to creatively tackle research problems and explore new avenues for molecular machine learning🔬🚀
The second day of the kickoff meeting was a big success with many inspirational talks, and an interactive poster session💻🌟
#community #MML
Today marked a great start of the second funding period of the SPP 2363 with the first day of our Kick-off meeting at the @Leopoldina in Halle.
Special thanks to Esther Heid for an truly inspiring talk connecting molecular representation, model architectures and reactivity! 🧪💻
SPP 2363 retweeted
We hire!
PhD positions from the DFG funded priority program @spp2363 ("Molecular Machine Learning") available in @GloriusGroup.
Link to SPP 2363: uni-muenster.de/SPP2363/
Excellence at the intersection of data science, cheminformatics & organic #chemistry - Congrats Florian on a poster award! @GloriusGroup, we use AI, HTE & HPC to advance catalysis & materials. 💻😀⚗️ #Cheminformatics #DataScience @spp2363
#MolecularMachineLearning @uni_muenster
Check out Prof. Schreiners interview in the upcoming edition of the "KI-Buzzer" magazine. He shares his view on AI and education🎓
kibuzzer.com/de/mag/v5/kibuz…
@prsgroupjlu
SPP 2363 retweeted
New Publication 👏
We are excited to share our latest paper, "Apax: A Flexible and Performant Framework for the Development of Machine-Learned Interatomic Potentials", published in the JCIM.
Read the full paper: pubs.acs.org/doi/10.1021/acs…
Code: github.com/apax-hub/apax
SPP 2363 retweeted
The @GloriusGroup 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/jobp…
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!
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! 🧠✨
Need to predict material properties? 🔮🧪
@ChengBingqing 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! 🤖✨
Solvent effects? Reaction dynamics? 🔄🌊
Fernanda Duarte (@fjduarteg) is now on stage at the #7thMML Symposium discussing how #MachineLearning Potentials (MLPs) balance efficiency & accuracy in modeling chemical reactions in solution! 🧪🤖
How can #MachineLearning accelerate the discovery of transition metal-containing materials?
🎤Heather J. Kulik (@KulikGroup) is kicking off the #7thMML Symposium!
🧪 “Getting from the Computer to Real World Materials Faster with Machine Learning”
