A fully funded 2-year post-doc position is available in the Computational Electronic Structure Theory group of Prof. Patrick Rinke at Aalto University in Helsinki, Finland. In this position, you will have a chance to make an impact by applying tools from artificial intelligence (AI) to the computational design of novel energy materials. Our objective is to enhance the functional properties of hybrid perovskite materials for solar energy technologies by AI-guided alloying, and in the process, generate a machine learning exploration tool for complex materials spaces.

We welcome candidates with a PhD in computational physics, chemistry or materials science who are curious about applied machine learning in natural sciences. Prior machine learning experience is a bonus, but not a must. We seek colleagues who enjoy coding, scripting and analytics, and are keen to push the boundaries of computational materials design. This project requires creative thinking and programming, as well as technical expertise in materials simulations and a broad understanding of electronic phenomena in solids.

More information on the position and application guidelines can be found here. The application deadline is 15.12.2020.