Dear Julians,
I am happy to announce an open PostDoc position on Bayesian methods for inverse materials design at the mathematics for materials modelling group (MatMat, https://matmat.org) at the Ecole Polytechnique Fédérale de Lausanne (EPFL).
We seek an outstanding candidate with a PhD in condensed matter physics or a related subject and a strong mathematical mindset. The position will employ the Julia-based materials simulation ecosystem, such as the Density-Functional ToolKit as well as Julia’s algorithmic differentiation capabilities to accelerate property-guided materials design.
The ideal candidate should have expertise with multiple of the following aspects: Bayesian techniques for surrogatisation, Bayesian optimisation, Julia programming, method development for inverse materials design, method development for density-functional theory, modelling of electronic conduction or related properties in materials.
Screening of candidates will start from 1st Februrary 2025 and continue until a suitable candidate has been found The expected starting date is the first half of 2025, but can be negotiated.
For more information and details how to apply, see Job Openings.
Feel free to contact me here or on michael.herbst@epfl.ch in case of further questions on the position.
Many thanks and happy new year !
Michael