9/7: Course introduction
9/14: Basic concepts in machine learning
9/21: AI for materials science
9/28: Practical concepts in machine learning 1
10/5 - 10/9: (Recorded lecture) Practical concepts in machine learning 2
10/12: Molecular dynamics simulations
10/19: Machine-learning interatomic potentials (MLIPs): theory
10/26: Run MLIPs with Claude code
Reports: How AI-based simulations will be applied to the student’s own research
11/2: MLIP practice - modelling, energy calculations, optimization, and MD simulations
11/9: MLIP practice - liquid & amorphous materials
11/16 - 11/20: (Recorded lecture) DFT calculations
11/23: MLIP practice - surface reactions
11/30: MLIP practice - ion conductivity calculations
12/7: MLIP practice - phonon & thermal conductivity calculations
12/14: AI beyond MLIPs in materials science
12/21: Project presentation - Use of materials simulation in your research