⚠️ Job offer ⚠️

Max-Planck-Institut für Kohlenforschung

📢 We're hiring!
The Qiu group at the Max-Planck-Institut für Kohlenforschung is looking for a #PhD student or #Postdoc in Physical Organic Chemistry.
Guanqi Qius group focuses on conceptualizing new principles of organic reactivity and #catalysis. The research program is not bound by any particular chemical transformation, yield, or selectivity. The goal is to demonstrate the concept through flexible sets of chemical reactions, and eventually generalize the concept towards a reaction design principle.
The position is funded by an European Research Council (ERC) Starting Grant (IntrinsicR).
📍 Mülheim an der Ruhr, Germany
🗓️ Apply by 15 November 2025
More details here 👉 https://lnkd.in/edjRZeeC

The wait is over! Microsoft Research is sharing Skala, the new exchange-correlation functional, marking a major milestone in the accuracy/cost trade-off in DFT. Help us learn from your testing so we can improve. Available on Azure AI Foundry and GitHub.

Skala is a neural network-based exchange-correlation functional for density functional theory (DFT), developed by Microsoft Research AI for Science. It leverages deep learning to predict exchange-correlation energies from electron density features, achieving chemical accuracy for atomization energies and strong performance on broad thermochemistry and kinetics benchmarks, all at a computational cost similar to semi-local DFT.

Trained on a large, diverse dataset—including coupled cluster atomization energies and public benchmarks—Skala uses scalable message passing and local layers to learn both local and non-local effects. The model has about 276,000 parameters and matches the accuracy of leading hybrid functionals.

https://labs.ai.azure.com/projects/skala/

https://github.com/microsoft/skala

🚀 Be part of Qiskit Fall Fest 2025 – the first-ever Quantum Computing festival in Andhra Pradesh. Learn, compete, innovate, and connect with bright minds.
⚡ Workshops • Lectures • Hackathons • Challenges – Unlock your Quantum journey. Register now!
🔗 quantum.rgukt.in

Follow social mediapages for more updates

Instagram: https://www.instagram.com/rguktap_qff2025?igsh=MW04ODdyMmxxdWFweQ==
Linkdln:
https://www.linkedin.com/company/rguktsklm-qff2025/

We built MARCUS - a free, open-source AI platform that extracts the millions of chemical structures trapped in PDFs in minutes instead of hours.

https://doi.org/10.1039/D5DD00313J

Cost-free CCSD(T) correlation energy calculator.

By Mateusz Witkowski, Szymon Śmiga, So Hirata, Pavlo O. Dral and Ireneusz Grabowski

"In our recent paper, “Ultrafast Correlation Energy Estimator” (https://pubs.acs.org/doi/10.1021/acs.jpca.5c04423), we propose a simple fragmentation scheme that assigns correlation energy to chemical bonds—the Correlation Energy per Bond (CEPB) method. CEPB provides near-zero-cost access to the correlation energies of very large systems while achieving ≈99.5% accuracy relative to CCSD(T)/CBS. Currently, CEPB is well-suited for rigorously evaluating the robustness of DFT and machine-learning models by supplying benchmark-quality reference data in regimes where canonical CCSD(T) is computationally prohibitive. An online calculator implementing CEPB is available at: https://www.home.umk.pl/~matwitkowski/."

Quantum chemical calculations for predicting the partitioning of drug molecules in the environment

Lukas Wittmann, Tunga Salthammer & Uwe Hohm

Regional and temporal trends in legal and illicit drug use can be tracked through monitoring of municipal wastewater, ambient air, indoor air, and house dust. To assess the analytical result for the selected environmental matrix, reliable information on the partitioning of the target substance between the different compartments is required. The logarithmic partition coefficients octanol/water (log KOW), octanol/air (log KOA) and air/water (log KAW) are usually applied for this purpose. Most drug molecules are semi-volatile compounds with complex molecular structures, the handling of which is subject to legal regulations. Chemically, they are often acids, bases, or zwitterions. Consequently, the physical and chemical properties are in most cases not determined experimentally but derived from quantitative structure–activity relationships (QSARs). However, the lack of experimental reference data raises questions about the accuracy of computed values. It therefore seemed appropriate and necessary to calculate partition coefficients using alternative methods and compare them with QSAR results. We selected 23 substances that were particularly prominent in European and US drug reports. Different quantum mechanical methods were used to calculate log KOW, log KOA, and log KAW for the undissociated molecule as a function of temperature. Additionally, the logarithmic hexadecane/air partition coefficient log KHdA ≡ L and the logarithmic vapor pressure of the subcooled liquid log PL were determined in the temperature range 223 < T/K < 333. Despite the sometimes high variability of the parameters, it is possible to estimate how an investigated substance distributes between air, water and organic material.

Read more at 👇
https://doi.org/10.1039/D5EM00524H

Hybrid DFT Quality Thermochemistry and Environment Effects at GGA Cost via Local Quantum Embedding
Click

József Csóka, Dénes Berta, and Péter R. Nagy
Journal of Chemical Theory and Computation 2025 21 (19), 9573-9586

https://pubs.acs.org/doi/full/10.1021/acs.jctc.5c01121

Quantum chemistry and large systems – a personal perspective by Frank Neese, creator of the ORCA Quantum Chemistry Software.

https://www.degruyterbrill.com/document/doi/10.1515/pac-2025-0587/html

Job Alert
Exciting postdoc position available: theoretical and experimental cryo-EM studies of flexible biomolecules. Competitive salary, collaborative environment at NYSBC and Flatiron Institute. Please share!! and contact: pcossio@flatironinstitute.org

We are saddened to share that the amazing Axel D. Becke has passed away. What a great loss for the Comp Chem field.

https://www.ufe.cz/volne-pozice/computational-molecular-modelling-research-assistant/ PhD position in Czech Republic

🚀 New Software Release!
Q-Shape 🎯 is an open-source tool for continuous shape measures (CShM) and molecular geometry analysis in coordination chemistry ⚗️🔬

✨ What is it used for?
🔹 Quantifies how close a coordination complex is to an ideal polyhedron (octahedron, tetrahedron, square planar, etc.)
🔹 Compares different structures and identifies distortions in molecular geometries
🔹 Studying ligand effects, electronic influences, and symmetry deviations in transition metal complexes
🔹 Transforms structural data into numbers you can analyze, compare, and publish 📊

🔒 Privacy Note: Q-Shape runs entirely in your browser. No data is uploaded or stored on external servers — all calculations stay safe on your device.

Access the repo: https://github.com/HenriqueCSJ/q-shape

Try it online: https://henriquecsj.github.io/q-shape/

HTA - An open-source software for assigning head and tail positions to monomer SMILES in polymerization reactions

https://doi.org/10.1186/s13321-025-01098-x

Can a Large Language Model (LLM) really understand chemical reactivity? oMeBench: Towards Robust Benchmarking of LLMs in Organic Mechanism Elucidation and Reasoning

Ruiling Xu, Yifan Zhang, Qingyun Wang, Carl Edwards, Heng Ji

Organic reaction mechanisms are the stepwise elementary reactions by which reactants form intermediates and products, and are fundamental to understanding chemical reactivity and designing new molecules and reactions. Although large language models (LLMs) have shown promise in understanding chemical tasks such as synthesis design, it is unclear to what extent this reflects genuine chemical reasoning capabilities, i.e., the ability to generate valid intermediates, maintain chemical consistency, and follow logically coherent multi-step pathways. We address this by introducing oMeBench, the first large-scale, expert-curated benchmark for organic mechanism reasoning in organic chemistry. It comprises over 10,000 annotated mechanistic steps with intermediates, type labels, and difficulty ratings. Furthermore, to evaluate LLM capability more precisely and enable fine-grained scoring, we propose oMeS, a dynamic evaluation framework that combines step-level logic and chemical similarity. We analyze the performance of state-of-the-art LLMs, and our results show that although current models display promising chemical intuition, they struggle with correct and consistent multi-step reasoning. Notably, we find that using prompting strategy and fine-tuning a specialist model on our proposed dataset increases performance by 50% over the leading closed-source model. We hope that oMeBench will serve as a rigorous foundation for advancing AI systems toward genuine chemical reasoning.

🔗 https://arxiv.org/abs/2510.07731v1

We are pleased to announce the release of alvaModel version 3.0.0, a major
update to our software for building, validating, and analyzing QSAR/QSPR
models.

This release introduces several important features aimed at expanding modeling
capabilities, improving interpretability, and streamlining the model
development workflow.

New Modeling Capabilities

Regression and Classification Models
- Decision Tree (Regression and Classification)
- Random Forest (Regression and Classification)
- Consensus Classification Model (weighted on reliability)

Customizable Model Parameters
Users can now define sets of custom parameters for:
- K-Nearest Neighbors (KNN)
- Support Vector Machine (SVM)
- Consensus (Classification)
- Decision Tree
- Random Forest

Applicability Domain
- New method: Bounding Box

Similarity Measures
- Dice and Cosine distances are now supported

Enhanced Evaluation Metrics

New Classification Scores
- AUROC (Area Under the Receiver Operating Characteristic Curve)
- F1 Score
- Matthews Correlation Coefficient (MCC)
- Cohens Kappa

Improved Visualization and User Interface

Model Comparison Features
- New interface for comparing multiple models
- Display of 95% confidence intervals for scores
- Automatic highlighting of best/worst scores
New comparison charts:
- Simultaneous Confidence Interval Plot
- Radar Plot

Classification Model View Enhancements
- New Reliability column
- Color-coded indicators for:
- Correct predictions
- Reliability
- Applicability Domain (A.D.)
- Colored Confusion Matrix with molecule filtering capability

Workflow and Usability Improvements
- Prediction of external datasets without the need for alvaRunner
- New Open Recent Project menu
- Batch model saving in automatic model generation
- Improved dataset management:
- Move or copy molecules between datasets
- Rename external variable columns
- Contextual popup menus for dataset and model tables

Charts and Visualization Enhancements
- Unified chart toolbar for easy selection of chart types and settings
- For regression models: R and RMSE are now displayed in plot legends
- For classification models: ROC Curve and PrecisionRecall Curve available


For an overview of the new features, you can watch the introduction video:
https://youtu.be/5TVcpxTdQAY

More information is available on the alvaModel product page:
https://www.alvascience.com/alvamodel

WE ARE HIRING !

Position Summary: The laboratory of Dr. Donald Weaver, Krembil Research Institute, and Department of Chemistry (University of Toronto) invites applications for one Postdoctoral Researcher Position in Computational/Theoretical Chemistry. Work will involve applications of molecular modelling methods (molecular dynamics/molecular mechanics/quantum mechanics calculations) to understanding neurochemical processes, developing in silico disease models and participating in a multi-disciplinary group focused on drug design for neurodegenerative disease.

Applicants should hold a PhD in Computational/Theoretical Chemistry (must be obtained within the previous 5 years) and have a strong background in the development and use of molecular modelling and electronic structure theory. The successful candidate will work in the Krembil Research Institute, which is part of the Toronto Western Hospital. We expect strong commitment, good communication skills and ability to work in a multidisciplinary environment with highly qualified professionals from international backgrounds.

Major topics of research include: Molecular dynamics simulations;
Molecular mechanics optimizations/protein modelling; DFT and molecular orbital ab initio calculations; Applications to neurochemistry, small molecule structure and hydration/solvation

Duties: Performing molecular modelling simulations; Performing molecular dynamics simulations; Performing molecular mechanics calculations; Performing molecular quantum mechanics calculations; Computer-aided drug design

Apply here:
https://lnkd.in/gmQrhxUz

🔗 https://www.linkedin.com/posts/donald-weaver-067a963_chemistry-computationalchemistry-theoreticalchemistry-activity-7392223121266827264-mJ2U?utm_source=share&utm_medium=member_desktop&rcm=ACoAADByb54BZAu0zfSJLooSdNdx0bXFCOsvoA0