Position:
PostDoc position in a joint project between IBM Research Zurich and EPFL Sion, under the supervision of Dr. Ivano Tavernelli and Prof. Berend Smit.

The position is part of the centre on Computational Design and Discovery of Novel Materials, NCCR MARVEL, created by the Swiss National Science Foundations in 2014.

Project:
Investigation of photocatalytic properties of Metal Organic Frameworks (MOFs) using a combination of first-principle and machine learning techniques.

Research:
Metal-organic frameworks (MOFs) consist of metal nodes that are connected by organic linkers. They are thus highly chemically tunable materials given the broad range of potential linkers and nodes that can be chosen for their synthesis. Their tunability has recently sparked interest for the development of new MOF photo-catalysts for energy-related applications such as hydrogen (H2) evolution and CO2 reduction. The sheer amount of potentially synthesizable MOFs requires to define descriptors that allow to predict their performance with this aim. The goal of this project is the investigation of the photocatalytic properties of existing MOFs (among which some are synthesized in the group pf Prof. Smit at EPFL Sion) and proposed chemical modifications that can improve their catalytic efficiency. In order to improve the sampling of the accessible chemical space, we also plan to combine first-principle calculations with the screening of large MOFs databases using suited descriptors derived in the group.

Desirable experience:
Knowledge of electronic structure methods (in particular DFT and TDDFT) for molecules and solid state materials. Experience on dynamics (ground state and excited states) and machine learning techniques for materials characterization and screening of databases.

If you are interested in a position, please send your CV to Ivano Tavernelli at the address [email protected] together with a motivation letter and 2 reference letters.