MLIP School 2026 — Dataset craft for machine-learned interatomic potentials
You will build a silicon dataset from scratch, fit ACE potentials, and learn why a low RMSE can still be a bad potential.
Two ways to work
In your browser
On your own machine
Run:
uvx mograder student https://mlipschool.uk/mograder.tomlYou will need your API key. You were given one on a printed slip at registration. Paste it into the notebook's API key field, and use the same key throughout — E2, E3 and C resume the potential you fit in E1, and models belong to the key that fitted them.
Work through the exercises in order: E1, E2, E3, then C. E1x is an optional extension — take it after E1 if you are ahead. It resumes nothing and spends none of your labels, so skipping it costs you nothing.