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MLFF Distillation & GCMC Integration - Internship

CuspAI· AI/ML
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Hybrid (London, UK), Hybrid (Cambridge, UK)Full-timePosted 3mo ago

About the role

Internship to develop fast, accurate machine learning force fields (MLFFs) for high-throughput Monte Carlo simulation and integrate them into the in-house framework kUPS, focusing on guest–host interactions in MOFs via distillation into lightweight potentials and GCMC integration.

Responsibilities

  • Distill MLFFs into fast student potentials optimised for Monte Carlo simulations.
  • Curate, version, and document training and validation datasets, including the distillation protocol and active-learning loops.
  • Run head-to-head validation campaigns comparing distilled MLFF against classical force-field baselines across a curated set of guest molecules, characterising accuracy, throughput, and failure modes.
  • Profile and optimise the pipeline for throughput, with focus on the MC inner loop where MLFF inference cost dominates.
  • Benchmark accuracy/speed trade-offs and document failure modes of the distilled model.
  • Collaborate with computational chemists on reference data generation, benchmark system selection, and validation strategy.
  • Contribute to a publication establishing MLFF-driven GCMC for MOF screening.

Qualifications

  • Currently enrolled in (or recently completed) a PhD or Master's programme in a relevant quantitative field (Physics, Chemistry, Chemical Engineering, Computational Science, Machine Learning, or similar).
  • Experience in adsorption modelling at the atomic scale.
  • Hands-on experience with molecular simulation methods (GCMC, MD, or both).
  • Comfortable working on Linux environments and managing simulation campaigns at scale.
  • Genuine interest in the application of ML to chemistry and materials science.

Skills

Required:ML-friendly knowledge distillationMolecular simulationDataset curation & active learningLinux & simulation campaigns

Benefits

  • A competitive salary: We value and reward impact and growth
  • Equity in CuspAI: You have a stake in the success of the company
  • Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays
  • ‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay
  • Professional development budget: We invest in your career development
  • Solve meaningful problems: Direct impact on materials science and sustainability through bleeding-edge technology
  • True interdisciplinary teamwork: Collaborative environment across AI research, computational chemistry, and experimental science
Last updated Aug 13, 2026. Interested? Apply on the company site.

About CuspAI

CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress.

CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress.

AImaterials
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