# PostDoc position "Gradient-accelerated inverse materials design"

**URL:** <https://discourse.julialang.org/t/postdoc-position-gradient-accelerated-inverse-materials-design/115965>\
**Category:** Jobs\
**Created:** [June 21, 2024, 7:40am UTC](https://discourse.julialang.org/t/postdoc-position-gradient-accelerated-inverse-materials-design/115965 "2024-06-21T07:40:27Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![mfh](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mfh/32/13787_2.png) [@mfh](https://discourse.julialang.org/u/mfh)\
**Post date:** [June 21, 2024, 7:40am UTC](https://discourse.julialang.org/t/postdoc-position-gradient-accelerated-inverse-materials-design/115965/1 "2024-06-21T07:40:27Z")

</div>

The [Mathematics for Materials Modelling](https://matmat.org) research group at EPFL is searching for a motivated PostDoc with a background in **Bayesian optimisation** and/or **surrogate modelling in atomistic simulations** to extend our team. See [matmat.org/jobs](https://matmat.org/jobs/#postdoc_position_gradient-accelerated_inverse_materials_design) for the details of the opening.

**Deadline:** Screening of candidates starts 1st August 2024.  
**Initial duration:** 18 months, extension possible given appropriate funding

 ![MatMat logo](https://global.discourse-cdn.com/julialang/original/3X/8/0/806549e4461bc887ccb62d60c23b2a4dc0c33125.png)

The activities of the MatMat group revolve around understanding modern materials simulations from a mathematical point of view – and to come up with ways to make such simulations faster and quantify their errors. You will become part of a young and energetic team, fully integrated with both the [mathematics](https://math.epfl.ch) and the [materials](https://imx.epfl.ch) institutes as well as multiple cross-disciplinary initiatives, such as the [NCCR MARVEL](https://nccr-marvel.ch/). Within the proposed topic you will be able to bring in your prior expertise, but also be able to get to know the exciting theory and practice of material modelling.

An interdisciplinary interest and the willingness to learn about the mathematical, physical and algorithmic underpinnings of state-of-the-art electronic structure theory is required. A core component of our work involves developing and extending Julia tools such as the [density-functional toolkit (DFTK)](https://dftk.org) or other packages of the wider [JuliaMolSim](https://github.com/JuliaMolSim) ecosystem. A solid knowledge of Julia is thus highly desirable for this position.

## Contact

Feel free to email with informal inquiries at michael.herbst@epfl.ch.