A fully funded PhD position is available in the Computational Electronic Structure Theory (https://www.aalto.fi/en/department-of-applied-physics/computational-electronic-structure-theory-cest) group of Prof. Patrick Rinke at Aalto University in Helsinki, Finland. In this position, you will have a chance to make an impact on the green and digital transition by applying tools from artificial intelligence (AI) to CO2 conversion. You will be developing data science and machine learning approaches and apply them to optimize and better understand catalyst materials and catalytic conversion processes.  

We welcome candidates with a Master’s degree in (computational) physics, chemistry or materials science who are curious about applied machine learning in natural sciences. Prior machine learning or Python 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 data-driven materials science and materials exploration. This project requires creative thinking and programming, as well as technical expertise in materials simulations and a broad understanding of surface science and catalysis.

More information on the position and application guidelines can be found here:  https://www.aalto.fi/en/open-positions/doctoral-candidate-in-ai-guided-co2-conversion  The application deadline is 25.2.2022.