Computational Catalysis of Oxide–Metal/Metal–Oxide Interfaces for CO₂ and CH₄ Conversion

This opportunity focuses on the theoretical investigation of heterogeneous catalysis at oxide–metal interfaces, with particular emphasis on ceria-based systems for CO₂ hydrogenation and methane activation.

The project combines state-of-the-art computational approaches, including periodic Density Functional Theory (DFT), hybrid functionals, machine learning-assisted structure search (e.g., GOFEE), and microkinetic modeling. Reaction mechanisms, active sites, and structure–activity relationships will be systematically explored under realistic conditions.

A key aspect is the strong integration with experimental research. Close collaboration with groups performing operando spectroscopy (AP-XPS, DRIFTS, STM) enables direct validation of theoretical predictions and provides a unique framework for understanding catalytic processes at the atomic scale.

The candidate will benefit from access to high-performance computing resources (e.g., MareNostrum) and advanced workflows for transition state calculations (NEB), machine-learning force fields, and global optimization.

This position offers an excellent environment for MSCA-PF applicants interested in computational catalysis, surface science, and sustainable energy processes, with structured supervision, interdisciplinary training, and strong support for proposal preparation and career development.