A post-doctoral position is open in the group of Dr. Pavlo Dral in College of Chemistry and Chemical Engineering at Xiamen University for the development of cutting-edge machine learning and quantum chemistry methods. The earliest starting date is January 2020. …
Post-doctoral Position Opening in Machine Learning in Quantum Chemistry Read more »
I am happy to announce that I am joining Xiamen University as an Associate Professor.
Prof. Walter Thiel passed away unexpectedly on August 23, 2019.
The mathematical and implementation details of the techniques available in MLatom: A Package for Atomistic Simulations with Machine Learning are reported.
Johannes Margraf and I have published our perspective on what semiempirical molecular orbital (SEMO) methods are and should be approximating in the article[1] dedicated to the 70th birthday of our PhD supervisor Tim Clark.
MLatom 1.0 release of my package for atomistic simulations with machine learning is now available.
We have introduced two new NDDO-based semiempirical quantum-chemical methods ODM2 and ODM3, which are more consistent and accurate than other existing methods of this type.
We comprehensively analyzed the validity of the NDDO (neglect of diatomic differential overlap) approximation, which forms the basis for most modern semiempirical quantum chemical methods.
We demonstrate that deep learning can be used to perform pure machine learning nonadiabatic excited-state dynamics of molecular systems.
Machine learning paves the way for massive simulations of nonadiabatic excited-state molecular dynamics.