Description
CuspAI is seeking an engineering intern to develop fast, accurate machine-learning force fields for high-throughput Monte Carlo simulations and integrate them into its kUPS simulation framework. The intern will distill equivariant models into lightweight student potentials, curate and document training and validation datasets, run accuracy and throughput comparisons against classical force fields, optimize inference pipelines, and collaborate with computational chemists on MOF screening and related publications. The role requires a relevant PhD or Master's programme, atomic-scale adsorption modelling experience, molecular simulation experience, and Linux proficiency.
