A postdoctoral position is available at CEA-Grenoble, France, on the theoretical search for and understanding of novel materials for energy conversion and storage. The successful candidate will develop different algorithms, including neural networks, for the fast computation of properties of solid compounds, and apply them to the calculation of finite-temperature phase stability and transport properties. She/he will integrate a materials modelling team with strong connections to various experimental and theoretical groups worldwide. More information about our research can be found at http://goo.gl/W3Do4y .

Grenoble is located at the foot of the French Alps, and it enjoys a rich scientific, technological and cultural environment.

Required qualifications:

-A recent PhD in computational/theoretical condensed matter physics, computational chemistry, or related discipline.

-A track record of publications in materials modeling.

-Strong programming and analytical skills.

Modeling experience on one or more of the following topics is a plus: machine learning, high throughput materials modeling, energy storage, data mining.

To apply: send a.s.a.p. a cover letter and CV, including publication list and contact information of at least three references, to [email protected]