Frugal Machine Learning and Density Functional Theory for the Design of Sustainable Catalytic Materials (M/F)
The French National Centre for Scientific Research (CNRS)
France
Summary
PhD position in data-efficient machine learning for CO2 hydrogenation to methanol on oxide-metal interfaces. Combine DFT and ML to model catalytic activity, develop transfer learning and ML potentials. Ideal for candidates with chemistry/physical chemistry/materials science and Python/HPC skills.
