A fully funded 2-year post-doc 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 work in a collaborative team with researchers from VTT Technical Research Centre of Finland. You will have a chance to make an impact on the green and digital transition by applying tools from artificial intelligence (AI) to neuromorphic computing. Neuromorphic devices realize neural networks directly on a chip. Our objective is to optimize existing and discover new materials for robust and low-power neuromorphic device components.  

We welcome candidates with a doctorate in (computational) physics, chemistry or materials science who are curious about applied machine learning in the natural sciences. Prior machine learning or Python experience is a strong 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 semiconductor physics and devices. We further appreciate willingness to travel, teach and mentor, collaborate and communicate science.

More information on the position and application guidelines can be found here: https://www.aalto.fi/en/open-positions/postdoctoral-position-in-ai-guided-materials-design-for-neuromorphic-computing The application deadline is 19.12.2022.