Chemistry, Biophysics and Coding
Joined June 2016
- Tweets 468
- Following 2,502
- Followers 1,390
- Likes 585
10 Photos and videos
Mark Waller retweeted
23 Jul 2024
Very exciting to share: AQuaRef- #CryoEM and XRD protein structure refinement with #MachineLearning #QM Teamwork by @MalgoBiczysko @Kavi_Dil @Zubatyuk @adrian_roitberg @waller_lab @hokru_science @PendingAI and @LBNLresearch team 💪
biorxiv.org/content/10.1101/… #compchem
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Mark Waller retweeted
20 Feb 2024
Pending AI has been invited to participate in the @AWS and @peakxvpartners Generative AI United States Delegation in Palo Alto, California this week. Our Vice President, Business Development, David Almeida Cardoso, PhD, is in attendance.
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Mark Waller retweeted
8 Feb 2024
🚨 Job alert! 🚨
Three (!) postdoctoral positions in quantum computing for chemistry
Total package: $119k – $148k p.a. for up to 4 years
Some details below; apply by 11 March here: tinyurl.com/yck44d43
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Mark Waller retweeted
9 Dec 2023
After 1.5 yeas our review “Integrating #QSAR modelling and deep learning in #drugdiscovery: the emergence of deep QSAR” in @NatRevDrugDisc is out! Great team effort with Alex Tropsha, Alexandre Varnek, Gisbert Schneider, and Art Cherkasov #compchem nature.com/articles/s41573-0…
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Mark Waller retweeted
17 Jun 2023
Delighted to share our recent work in which we developed MeGen, an RL model, to efficiently generate low-energy Ga cluster 3D structures. MeGen outperforms the conventional approach in time and resources for generating ground-state (GS) geometries and low-lying isomers.
Great new work by @RohitModee U Deva Priyakumar et al @iiit_hyderabad @csir_ncl @AcSIR_India - 'MeGen - generation of gallium metal clusters using #reinforcementlearning' - bit.ly/42FguRu #machinelearning #materials #condmat #metals #algorithms #DFT #electronicstructure
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Mark Waller retweeted
3 Jan 2023
It's back!
AI in Drug Discovery 2022 - A Highly Opinionated Literature Review
practicalcheminformatics.blo…
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Mark Waller retweeted
10 Nov 2022
Hey, chemtweeps, @gabepgomes & I have a joint postdoc #chempostdoc opening. The position will focus on developing ML/AI algorithms for autonomous experimentation at @CarnegieMellon Cloud Lab cloudlab.cmu.edu/. Opps to work with @NSF_CCAS! #compchem
apply.interfolio.com/117136
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Mark Waller retweeted
12 Sep 2022
The ELLIS ML4Molecules workshop will also happen this year on November 28 in VIRTUAL format!
Please find the announcement and the call for papers here: moleculediscovery.github.io/…
Looking forward to your contributions!
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Mark Waller retweeted
22 Sep 2022
A new paper just published in @JCIM_JCTC! Auto3D: Automatic Generation of the Low-Energy 3D Structures with ANI Neural Network Potentials. Collaboration with @adrian_roitberg #compchem #MachineLearning pubs.acs.org/doi/full/10.102…
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Mark Waller retweeted
20 Sep 2022
I can't believe that our book “Quantum Chemistry in the Age of Machine Learning” is finally out!
I can't express enough my gratitude to everyone involved!
dr-dral.com/book-quantum-che…
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Mark Waller retweeted
30 May 2022
NMR Spectrum to Structure @iiit_hyderabad @kcisatiiith @IHUB_Data @yashaswi_201 @JPhysChem #compchem #NMR #drugdesign #chem #MachineLearning
30 May 2022
. @JPhysChem Deep Reinforcement Learning for Molecular Inverse Problem of NMR Spectra to Molecular Structure, Bhuvanesh Sridharan, Sarvesh Mehta, Yashaswi Pathak, U. Deva Priyakumar* @deva_priyakumar @iiit_hyderabad pubs.acs.org/doi/10.1021/acs… #NMRchat #NMR
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Mark Waller retweeted
7 Jun 2022
I am beyond excited to announce that QMugs, our large open-source database of drug-like molecules alongside their computed quantum mechanical properties, is now available on @ScientificData! 🧵[1/5]
(work w. @clemensisert & @atzkenneth)
nature.com/articles/s41597-0…
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Mark Waller retweeted
10 Feb 2022
We develop a new #MachineLearning scheme for protein pKa. It is based on representation learning & combines atomic environment vector (AEV) and learned QM representation from ANI-2x neural network potential. Our latest paper in @ChemicalScience pubs.rsc.org/en/content/arti… #compchem
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Mark Waller retweeted
21 Feb 2022
A machine-learning model as Mat2Spec based on probabilistic embedding enables to predict materials’ phonon density of states and electronic density of states instead of single scalar properties go.nature.com/3H1KYCp #mlchem#compchem @johnmgregoire @Caltech @BerkeleyLab @Cornell
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Mark Waller retweeted
21 Feb 2022
Our ML seminar @EPFL_CHEM_Tweet starts again tomorrow at 15.15 with a talk by @jmhernandez233
memento.epfl.ch/event/machin…
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