Internship - MLFF Distillation & GCMC Integration

About the role

CuspAI is seeking an engineering intern to join our chemistry team for a 3-month project focused on accelerating material discovery. You will develop machine learning force fields for high-throughput Monte Carlo simulations and integrate them into our proprietary kUPS framework.

Key facts

What you'll do

• Distill machine learning force fields into lightweight student potentials for Monte Carlo applications.
• Manage, version, and document datasets, including distillation protocols and active-learning loops.
• Conduct validation studies comparing distilled models against classical force-field baselines.
• Profile and optimize simulation pipelines to improve throughput within the Monte Carlo inner loop.
• Partner with computational chemists to define benchmarks and contribute to research publications regarding MOF screening.

Requirements

• Current enrollment in or recent graduation from a PhD or Master's program in Physics, Chemistry, Chemical Engineering, Computational Science, Machine Learning, or a related field.
• Practical experience with atomic-scale adsorption modeling.
• Hands-on proficiency with molecular simulation techniques such as GCMC or MD.
• Ability to work effectively in Linux environments and manage large-scale simulation campaigns.
• Strong interest in applying machine learning to chemistry and materials science.

Nice to have

• Knowledge of modern machine learning force fields.
• Experience with model compression or knowledge distillation for scientific applications.
• Familiarity with active learning workflows for atomistic data.
• Experience generating DFT data and curating atomistic datasets.
• Proficiency with established simulation software packages.
• Background in porous materials, MOFs, or gas adsorption.
• Familiarity with classical force fields for MOF simulation.
• Research publications in top-tier computational chemistry or machine learning venues.

Skills & tools

• Machine Learning Force Fields (MLFF)
• GCMC / MD simulations
• Linux
• kUPS (internal framework)
• Python / Scientific computing stack

Practical notes

• Benefits include 28 days of holiday plus public holidays, a professional development budget, and parental leave (26 weeks for primary caregivers, 12 weeks for secondary).
• CuspAI is an equal opportunity employer and provides reasonable accommodations for the interview process upon request.