Model systems and interaction potentials. Short review of statistical mechanics. Monte Carlo methods, molecular and stochastic dynamics, quantum simulations. Advanced simulation techniques; e.g. free energy estimation, non-equilibrium molecular dynamics. Applications to polymers, surfaces, gels, biomolecules.

The objective of this course is to provide students with a strong conceptual and practical foundation in molecular simulation, with particular emphasis on Molecular Dynamics (MD). Students will learn the statistical-mechanical principles underlying molecular simulations, the essential ideas of Monte Carlo sampling, and the algorithms, models, and analysis techniques required to design and interpret reliable MD simulations. The course will also introduce advanced sampling and rare-event methods, including umbrella sampling, replica exchange molecular dynamics, metadynamics, and forward flux sampling, with emphasis on understanding when and why different approaches are appropriate. In addition, students will gain introductory exposure to machine-learning applications in molecular simulation.