The recently established Mathematics for Materials Modelling research group at EPFL is searching for a PhD student as well as a postdoc to extend our team.
We are an interdisciplinary group and part of both the mathematics as well as the materials science institutes at EPFL. Our research centres on bringing insight from maths to materials modelling, with the aim to understand simulation error and improve robustness of existing schemes. For this work an interdisciplinary interest and the willingness to learn about the mathematical, physical and algorithmic underpinnings of state-of-the-art electronic structure theory, such as density-functional theory (DFT), is required.
The development of Julia packages (e.g. the density-functional toolkit (DFTK)) is a core component of our work and knowledge of Julia is thus highly desired.
The PhD project concerns the development of Self-adapting numerical methods for high-throughput DFT simulations and targets a candidate with a background in programming, computational mathematics or computational physics.
The postdoc position concerns the Determination of uncertainties due to DFT model parameters and targets a candidate with a background in Bayesian modelling, Bayesian regression, uncertainty quantification ideally in an inverse design context.
Further information and instructions how to apply can be found on matmat.org/jobs.