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 work in the EU Marie Curie training network EUSpecLab. You will have a chance to make an impact on heterogeneous catalysis. Our objective is to develop a data-driven approach for analysing infrared spectra of in-situ catalyst characterization.    

We welcome candidates with a Master’s degree 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 machine learning in spectroscopy. This project requires creative thinking and programming, as well as technical expertise in materials simulations, machine learning 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-machine-learning-for-spectroscopy The application deadline is 6.6.2022.