Simulations are a crucial ingredient to develop new materials. At the Mathematics for materials modelling research group our mission is to make practical modelling workflows more efficient and reliable by importing mathematical insights into practical simulation schemes. Here our focus is the development of faster algorithms as well as a rigorous understanding of simulation error across the modelling scales.
You can learn more about our work by taking a look at our research topics, our publications, our demo notebooks, the software we develop. If you are interested and you want to work with us, feel free to take a look at our job openings. We also offer student projects at various levels.
epfl-matmat github organisation
Michael Herbst's website
29.06.2026 - 03.07.2026 Noé has been invited to give a talk in the "new ideas in molecular dynamics" minisymposium at SciCADE 2026 in Edinburgh, Scotland.
Noé will give a presentation about his recent work on machine learning quasi-stationarity diagnostics for accelerated MD algorithms
29.06.2026 Michael co-organises the minisymposium Advancing atomistic materials modeling with GPUs, novel algorithms, and error-controlled methods (jointly with Laura Grigori, EPFL, and Iurii Timrov, PSI) at the Platform for Advanced Scientific Computing (PASC) conference in Bern, Switzerland. He will also give the introductory talk of the minisymposium titled Trustworthy materials simulations: Practical error control techniques in DFT
09.07.2026: New publication Our article Efficient Krylov methods for linear response in plane-wave electronic structure calculations has been published today in SIAM Journal of Scientific computing.
This work is the outcome of Bonan's master thesis in the MatMat group, where he worked on inexact Krylov methods to accelerate typical density-functional perturbation theory calculations.
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DFTK: The density-functional toolkit