MOLFORCE project funded by the State Research Agency

Our project A unifying framework for classical and machine learning molecular force fields (MOLFORCE, PID2025-174682NA-I00) has been selected for funding in the 2025 call for Proyectos de Generación de Conocimiento of the Agencia Estatal de Investigación (MICIU/AEI). The four-year project starts in 2026.

Classical force fields are fast but have limited accuracy, while machine learning potentials are accurate but too expensive for large systems. MOLFORCE connects the two by using the same models of non-covalent interactions (electrostatics, induction, dispersion and exchange repulsion) in both. We will build these models into next-generation ML/MM potentials and into machine-learned classical force fields, and apply them to enzymatic catalysis and to the self-assembly of perylenediimides.

The project also includes a four-year FPI predoctoral contract, so we are looking for a PhD candidate to start in early 2027. Applicants should hold a Master’s degree in chemistry, physics, data science, computer science or a related field and have programming experience in Python. If you are interested, send your CV, academic transcripts and the contact details of two referees to kirill.zinovjev@uv.es.